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LSAY user guide Y06 March 2013 update

1. 1 2 3 4 5 Employment 6 Current 7 8 9 1 Social 0 Health living arrangements and finance 11 General attitudes Data elements Data elements represent variables that are common within and between waves In some instances a data element may represent a single variable when not collected across multiple waves Information about each data element is contained in the supplementary sections Data elements A to D of this User guide They can be accessed at lt www lsay edu au publications 2258 html gt under the supporting documents tab This series of data element documents are identified by their major and sub major topic area An overview of these data element documents is given in table 4 For each data element the following information is provided where applicable Data element the data element name Purpose the information provided by the data element Variables the variable name s which correspond to this data element Variable type whether the variable s is are in numeric or character format Variable label includes the question number where applicable and a short description of the variable s Question the question wording for the variable s Values the possible values the variable s can take and corresponding formats Base population a description of and the syntax for the number of respondents required to answer the question Notes other informa
2. Data users are encouraged to read the documents outlined in table 2 to better understand the PISA variables and data Plausible values In PISA student assessment is undertaken using 13 different test booklets and students are randomly assigned one of the booklets In order to counteract any biases resulting from the use of different text booklets the OECD calculates plausible values Plausible values allow for the fact that there is measurement error at the individual level through differing questionnaires and the determination of these plausible values takes this error into account For each student five plausible values have been calculated for each of the three domains reading mathematics and science and for five science sub domains interest in science support for scientific enquiry explaining phenomena scientifically identifying scientific issues and using scientific evidence Data users are encouraged to read the documents outlined in table 2 to better understand the construction and use of plausible values in LSAY Table 2 PISA technical documents Technical report paper Web address PISA 2006 Data analysis manual lt http www oecd org document 38 0 3343 en 32252351 322361 91 42609254 1 1 1 1 00 htm gt PISA 2006 Technical report lt http www oecd org dataoecd 0 47 42025182 pdf gt PISA 2006 Australian country report Exploring lt http www acer edu au documents PISA2006 Report pdf gt scientific liter
3. Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Leisure Hours spent watching TV 1 Hours spent listening to music 1 Hours spent playing sport 1 Hours spent reading for pleasure 1 Hours spent doing unpaid volunteer work Go to the library 1 1 1 1 Read books 1 1 1 1 Read newspapers or magazines 1 1 1 1 Use the internet 1 1 1 1 Play computer video games 1 1 1 1 Play sport or do exercise 1 1 1 1 Community activities 1 1 1 1 Go to church place of worship 1 1 1 1 Volunteer 1 1 1 Interests Learning new things 1 Thinking about why the world is in its i current state Finding out why things happened 1 Finding out more about things you do 1 not understand Finding out more about a new idea 1 Finding out how things work 1 Improving your skills after starting work 1 Learning new skills after starting work 1 Life satisfaction The work you do 1 1 1 1 1 What you do in your spare time 1 1 1 1 1 How you get on with people 1 1 1 1 1 The money you get each week 1 1 1 1 1 Your social life 1 1 1 1 1 Your independence 1 1 1 1 1 Your career prospects 1 1 1 1 1 Your future 1 1 1 1 1 Your life at home 1 1 1 1 1 LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Your standard of living 1 1 1 1 1 The way the country is run 1 1 The state of the economy 1 1 Where you live 1 1 1 1 1 Your life as a whole 1 1 1 1 1 Job aspirations Type of job expect at age 30 ISCO 1
4. Section J General attitudes The Y06 questionnaires can be accessed at lt www lsay edu au data 31271 html gt Table 1 provides a summary of the technical papers available ae LSAY 2006 cohort user guide The LSAY data The LSAY datasets are large and particularly complex About 700 variables are collected on average across each wave culminating in almost 3000 variables across the entire dataset To improve accessibility of the LSAY datasets data have been grouped into common themes called topic areas Topic areas The topic areas comprise four hierarchical levels Major topic areas are the broadest topic area There are four major topic areas Sub major topic areas are subdivisions of the major topic areas There are 11 sub major topic areas Minor topic areas are subdivisions of the sub major topic areas There are about 80 sub major topic areas Data elements are subdivisions of the minor topic areas There are more than 900 data elements Figure 2 LSAY hierarchical levels Major topic area Sub major topic area 1 Sub major topic area 2 Minor topic area 1 Minor topic area 1 Data element 1 Minor topic area 2 Data element 2 Minor topic area Minor topic area 2 Data element 3 etc Minor topic area 3 Data element 4 etc Data element 5 etc The four major topic areas are Demographics Education Employment and Social The divisions of these major topic areas into sub major topic
5. Specific data requests A specific data request allows you to request specific tables and or data analysis to be undertaken by NCVER without having to obtain full sets of the data A specific data request can be made to lt lsayrequests ncver edu au gt There are fees and charges applicable for all data requests that require more than one hour to prepare Please refer to NCVER s policy on charging lt http www ncver edu au statistic 21075 html protocols gt LSAY data releases Information about the latest LSAY data releases is available from the LSAY website lt www lsay edu au data latest html gt You may also reguest to be notified of recent LSAY releases which include publications and data releases by subscribing to NCVER s LSAY alert page at lt http www lsay edu au subscribe html gt For further information see the section on Using this guide registration NCVER FO Data restrictions Data use is restricted to research data are not to be used for commercial or financial gain In addition LSAY data users must agree to refrain from reporting student achievement information by school sector for the Y03 and Y06 cohorts This reflects permission reguirements agreed at the time the data were collected Further conditions of use are outlined in the LSAY User undertaking form which is available from the ADA LSAY information page http www ada edu au longitudinal lsay The conditions of use are
6. Type of job expect at age 30 verbatim 1 Type of job expect at age 30 Science related Aspirations fluence of family 1 nfluence of friends 1 nfluence of teachers 1 nfluence of media 1 nfluence of career advisors 1 nfluence of information from employers fluence of jobs work experience 1 Personal goal 1 1 Volunteer Canvassing campaigning fundraising 1 Unpaid member of board or committee 1 Provide information 1 Help organise activities 1 Coaching teaching 1 Collect serve or deliver food 1 Provide health care support counselling Other 1 Outcomes Job related skills 1 Outcomes Helped get a job 1 NCVER Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Leisure Hours spent watching TV 1 Hours spent listening to music 1 Hours spent playing sport 1 Hours spent reading for pleasure 1 Hours spent doing unpaid volunteer work Go to the library 1 1 1 1 Read books 1 1 1 1 Read newspapers or magazines 1 1 1 1 Use the internet 1 1 1 1 Play computer video games 1 1 1 1 Play sport or do exercise 1 1 1 1 Community activities 1 1 1 1 Go to church place of worship 1 1 1 1 Volunteer 1 1 1 Interests Learning new things 1 Thinking about why the world is in its i current state Finding out why things happened 1 Finding out more about things you do 1 not understand Finding out more about a new idea 1 Finding out how things work 1 Improving your sk
7. lt sible value in reading Plausible value in science Plausible value in interest in science Plausible value in support for scientific inquiry Pla phenomena scientifically lt sible value in explaining Pla issues lt sible value in identifying scientific Plausible value in using scientific evidence LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Time spent learning Science 3 Maths 3 Language 3 Other 3 Out of school 6 Perceptions about self na ekodi Importance Science 1 Importance Maths 1 Importance English 1 Subject English 1 Subject Maths 1 Subjects Overall 1 Life at school 30 Coping 6 Views on science Science enjoyment 5 Science self efficacy 8 Science value 10 Science activities 6 Science information source 6 Photosynthesis Science information source Continents 6 Science information source Genes 6 Science information source 6 Soundproofing Science information source Climate 6 change Science information source Evolution 6 Science information source Nuclear 6 energy Science information source Health 6 Science interest 8 NCVER Science enjoyment index Science self efficacy index Science value index Science activities index Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Science interest index 1 Scien
8. lt http www oecd org dataoecd 0 47 42025182 pdf gt The PISA 2006 data analysis manual for both SAS and SPSS users is available from lt http www oecd org document 38 0 3343 en 32252351 32236191 42609254 1 1 1 1 00 html gt The PISA 2006 country report Australia Exploring scientific literacy how Australia measures up is available from lt http www acer edu au documents PISA2006 Report pdf gt gt LSAY 2006 cohort user guide Accessing the data LSAY datasets are deposited annually with the Australian Data Archive ADA at the Australian National University in Canberra Permission to use the data and access reguirements are managed by the Australian Data Archive Data access reguires authorisation from the Data Archive Manager The data can be accessed by completing the Application to access LSAY restricted data form and the LSAY User undertaking form available from the Australian Data Archive LSAY information page lt http www ada edu au longitudinal lsay gt returning the completed forms via email to the Australian Data Archive at lt ada anu edu au gt Part of NCVER s role is to promote and encourage the use of the LSAY data If you have any feedback or queries about the data and how to access it please contact NCVER Email lt lsayrequests ncver edu au gt LSAY hotline 1800 825 233 Australian Data Archive email lt ada anu edu au gt phone 02 6125 2200 fax 02 6125 0627
9. Countries participating in PISA are able to introduce country specific guestions into PISA questionnaires referred to as national options questions Examples of national options data items included in PISA 2006 administered in Australia include Indigenous status and participation in work experience For this reason in addition to the publicly available PISA international dataset a separate national dataset is created for Australia that includes these national options questions Some variables available from the international dataset are omitted from the national dataset for example country In addition some minor differences may exist between the two versions of the dataset for example the way missing or not applicable values have been assigned to observations or whether the variables are in numeric or character format The PISA international student and school datasets are available from the OECD PISA database lt http pisa2006 acer edu au downloads php gt LSAY data can be matched to the PISA international datasets by filtering for Australian records using the country identifiers CNT COUNTRY and using student and school identifiers STIDSTD and SCHOOLID G LSAY 2006 cohort user guide It is recommended that data users wishing to make international comparisons using PISA data download the international dataset available from the OECD 2006 PISA international database located at lt http pisa2006 acer edu au downloads php gt
10. as follows 1 Use of the material is restricted to statistical purposes This means the user can only use the material to produce information of a statistical nature Examples of such uses are a the manipulation of data to produce means correlations or other descriptive summary measures the estimation of population characteristics from sample data the use of data as input to mathematical models and for other types of analyses for example factor analysis the provision of graphical and pictorial representation of characteristics of the population or sub sets of the population 2 The material is not to be used for any non statistical purposes or for commercial or financial gain without the express written permission of the Australian Data Archive National Manager Examples of non statistical purposes include but are not limited to a transmitting or allowing access to the data in part or whole to any other person department or organisation not a party to this undertaking attempting to match unit record data in whole or in part with any other information for the purposes of attempting to identify individuals 3 Statistical tables graphs etc obtained from analysis of these data may be further disseminated provided that the user a identifies the primary investigators data series and version number and data distributors by including the bibliographic reference for the data file acknowledges another
11. section Relevant data elements can be identified by navigating to a major topic area of interest for example Education identifying a sub major topic area of interest for example Post school education identifying a minor topic area of interest for example Current study inspecting the data elements available within that minor topic area for example Month started study The number of times that data element appears within a wave is shown in the column corresponding to the particular wave Before using and or analysing the variables data elements selected it is important to consider variable attributes such as question wording variable values classifications used and base populations data elements which appear more than once in a wave data elements which appear more than once across waves for longitudinal analysis data elements of the same name across other topic areas if applicable other data elements that may be closely linked in a topic area or across other topic areas ae LSAY 2006 cohort user guide Variable naming conventions PISA variables PISA variables only exist in wave 1 of the Y06 cohort and have a separate variable naming convention Naming conventions for different types of PISA variables are summarised in Table 5 The student guestionnaire instruments for PISA are comprised of the following two components the student questionnaire ST the information communication techn
12. Main reason 1 2 2 2 2 Changed left employer Same employer 2 2 2 2 2 Circumstances of changing employer 2 2 2 2 2 Reason Offered better job 2 2 2 2 2 Reason Boss other people at work 2 2 2 2 2 Reason On the job training 2 2 2 2 2 Reason Travelling transport 2 2 2 2 2 Reason Health personal reasons 2 2 2 2 2 Reason Main reason 2 2 2 2 2 Way in which next job was better 2 2 2 2 Month changed employer 2 2 2 2 2 Year changed employer 2 2 2 2 2 Changed stopped apprenticeship traineeship NCVER Reason Offered better job Reason Pay Reason Job prospects Reason Type of work Reason Boss other people at work Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Reason On the job training 1 1 1 1 1 Reason Off the job training 1 1 1 1 1 Reason Study training too difficult 1 1 1 1 1 Reason Travelling transport 1 1 1 1 1 Reason Health personal reasons 1 1 1 1 1 Reason Main reason 1 1 1 1 1 Satisfaction with study Problem solving skills 1 1 1 1 1 Analytic skills 1 1 1 1 1 Ability to work as a team member 1 1 1 1 1 Confidence in tackling unfamiliar i 1 1 i i problems Communication skills 1 1 1 1 1 Work planning 1 1 1 1 1 Overall satisfaction 1 1 1 1 1 mproved career prospects 1 1 1 1 1 Helped make contacts 1 1 1 1 1 mpressions Like being tertiary student 1 1 1 1 1 mpressions Student life suits you 1 1 1 1 1 mpressions Like campus atmosphere 1 1 1 1 1 mpressions St
13. Other 1 Language spoken at home All 1 Socioeconomic status Respondent s ISEI score 1 Cultural possessions index 1 Educational resources index 1 Household possessions index 1 Wealth index 1 Economic social and cultural status index NCVER Topic map 2 Demographics Parent Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Country of birth Mother s country of birth Mother s country of birth Other Mother s country of birth All Father s country of birth Father s country of birth Other Father s country of birth All Occupation Mother s occupation ISCO Mother s occupation White blue collar classification Mother s occupation Science related Mother works in job business Mother works full part time Mother s occupation ANZSCO Mother s main activity Other Father s occupation ISCO Father s occupation White blue collar classification Father s occupation Science related Father works in job business Father works full part time Father s occupation ANZSCO Father s main activity Other Parents occupation White blue collar classification Parents occupation Science related Education Mother s schooling Mother s qualifications Post secondary training certificate Mother s qualifications Post secondary training qualification Mother s qualifications University Mother s highest education level
14. XVET2009 XVET2010 One respondent who previously commenced and did not complete study in a bachelor degree or higher level gualification and had missed their last interview was incorrectly derived as having never commenced study in a bachelor degree or higher level qualification This derivation has been corrected so that this respondent is now derived as having commenced but not completed a bachelor degree or higher level qualification N Changes to Study status in VET due to corrections made to Current qualification level Changes to Study status in VET due to corrections made to Current qualification level 11 Changes to Study status in VET due to corrections made to Study status in VET in previous year One respondent who had indicated in a previous interview that they had commenced VET study training but did not confirm that course of study training in the current interview was derived as having commenced but not completed study in VET This derivation has been modified and this respondent is now derived as having never commenced VET study Some respondents who had returned to school and had indicated in a previous interview that they had commenced VET study training were not able to provide the outcome for that VET study but were recorded as having commenced but not completed that VET study training This derivation has been modified and these respondents are now derived as having never commenced VET study Changes
15. job seeking behaviour including whether they were looking for work job search activity details and problems looking for work Topic map 9 Employment Not in the labour force contains respondents main activity while not in the labour force and their intentions for seeking employment or commencing study Topic map 10 Social Health living arrangements and finance contains information about respondents living arrangements household possessions children marriage disability and health including associated funding government payments housing payments and financial circumstances Topic map 11 Social General attitudes contains information about what respondents do in their leisure time their life satisfaction job and life aspirations and any volunteer work undertaken ae LSAY 2006 cohort user guide Topic map 1 Demographics Student Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Place of residence State 1 1 1 1 1 Postcode 1 1 1 1 1 Gender Gender 1 1 Indigenous status ATSI 1 Date of birth age Age 1 Date of birth Month 1 Date of birth Year 1 Date of birth 1 Date of birth SAS date 1 Country of birth Country of birth 1 Country of birth Other 1 Country of birth All 1 Immigration status 1 Immigration status Australian definition 1 Age of arrival 1 Language spoken at iome Language spoken at home 2 Language spoken at home
16. metropolitan or non metropolitan as strata Within each school 50 students aged 15 years were selected at random In schools with fewer than 50 students all 15 year olds were selected Smaller jurisdictions and Indigenous students were oversampled to ensure that reliable results could be produced by state and Indigenous status These students were contacted in 2007 to undertake follow up telephone interviews as part of the LSAY program This interview collected further information on the respondent s school experience school and post school intentions school leavers and their transitions from school post school study employment living arrangements finance health and general attitudes Since 2007 respondents have been contacted annually using computer assisted telephone interviews CATI Further information about the survey design for PISA 2006 can be found from the PISA 2006 Technical report which can be accessed at lt http www oecd org dataoecd 0 47 42025182 pdf gt PISA 2006 Australian country report Exploring scientific literacy how Australia measures up which can be accessed at lt http www acer edu au documents PISA2006 Report pdf gt Response rates Table 8 shows the sample sizes and response rates for each wave of the LSAY Y06 cohort from 2006 Table 8 Sample sizes and response rates LSAY Y06 Wave year 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 ca vung 15 7 16 7 177 18 7 19 7 20 7 Sample size n 1
17. 1800 825 233 Email lt lsay ncver edu au gt Telephone 61 8 8230 8400 Website lt www lsay edu au gt Facsimile 61 8 8212 3436 1 Replaced in December 2007 by the Department of Education Employment and Workplace Relations LSAY 2006 cohort user guide Using this guide This User guide has been developed for users of the LSAY data The guide endeavours to consolidate existing technical documentation and other relevant information into a single document thereby improving data accessibility and promoting wider use of the LSAY data To promote effective use of the data the guide aims to address all aspects of LSAY data including information about how to access the data data restrictions variable naming conventions the structure of the data using topic areas topic maps and data elements classifications and code frames used weights and derived variables A series of additional documents Data elements A to D complement this User guide Data elements represent variables that are common within and between waves These documents contain information about the data elements including the variables they cover the valid values or response options for each variable and additional notes where applicable Information about the data elements documentation is contained in the section The LSAY data sub section Data elements Users may also find the metadata workbook useful The workbook provides a listing of all varia
18. ISCED LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Mother s qualifications Post secondary qualification Mother s qualifications Post secondary qualification type Father s schooling Father s qualifications Post secondary training certificate Father s qualifications Post secondary training qualification Father s qualifications University Father s highest education level ISCED Father s qualifications Post secondary qualification Father s qualifications Post secondary qualification type Parents highest education level ISCED Parents highest education level years Socioeconomic status Mother s ISEI score Father s ISEI score Parents ISEI score NCVER Topic map 3 Education School Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 School characteristics Geographic location School state School sector School postcode School identifier School offers IB 1 Student characteristics At school At school at last interview Year level Study program Student identifier ISCED level ISCED program ISCED orientation Studying for IB Changed schools Changed schools Month Changed schools Year Current school level derived variable Student achievement Plausible value in maths lt Pla
19. N CNTFAC_E and normalised weights CNTFAC_N For further information on PISA weights see the PISA 2006 Data analysis manual Indices AGE Student and school level simple and scaled indices tend to be HISCED descriptive rather than adopting a naming convention CULTPOSS LSAY standard variables Most variable names are constructed using four pieces of information the questionnaire instrument the survey wave the questionnaire section and the question number The character L is used to identify the survey instrument where L represents the LSAY survey instrument as opposed to the PISA survey instrument A wave identifier is used to identify the survey wave from wave 2 when the LSAY survey instrument is first used The second survey wave is allocated a B the third survey wave is allocated a C etc The section identifier is used to identify the section of the questionnaire The question identifier is used to identify the question number LSAY 2006 cohort user guide For example the variable LBA009 refers to the LSAY survey instrument denoted by the first character L wave 2 denoted by the second character B section A denoted by the third character A question 9 denoted by the last three characters 009 Figure 9 LSAY standard variable naming convention a LSAY non standard variables There are a series of other variables that do not take the standard variable naming con
20. Taught to develop formal study plan by friend acquaintances Taught to develop formal study plan by recruitment employment agencies Taught to write resume Taught to write resume at school Taught to write resume by family Taught to write resume by myself Taught to write resume by career expos advisors Taught to write resume by other source Taught to write resume by social community workers Taught to write resume by the Job Guide Taught to write resume by the media Taught to write resume through education Taught to write resume by friend acquaintances Taught to write resume by recruitment employment agencies Taught to prepare for job interview Taught to prepare for job interview at school LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 NCVER Taught to prepare for job interview by family Taught to prepare for job interview by myself Taught to prepare for job interview by career expos advisors Taught to prepare for job interview by other source Taught to prepare for job interview by social community workers Taught to prepare for job interview by the Job Guide Taught to prepare for job interview by the media Taught to prepare for job interview through education Taught to prepare for job interview by friend acquaintances Ta
21. a fut Lower limit Upper limit Year 12 1660 19 8 0 52 2 63 18 78 20 82 Year 11 5266 62 8 0 65 1 04 61 53 64 07 Year 10 1411 16 8 0 54 3 21 15 74 17 86 Year 9 or below 43 0 51 0 11 21 44 0 29 0 73 Total 8380 100 Table 11 Estimates standard errors RSEs and confidence limits for highest school level completed Y06 cohort in 2008 for a small sample remote respondents Year level Frequency Standard RSE 95 confidence interval error of set ae Lower limit Upper limit Year 12 72 42 1 5 96 14 16 30 42 53 78 Year 11 76 44 6 6 02 13 49 32 80 56 40 Year 10 23 13 2 3 68 27 88 5 99 20 41 Year 9 or below 1 0 12 0 12 100 56 0 12 0 35 Total 172 100 Notes Estimate has a relative standard error greater than 25 Estimate has a sample size of fewer than five Using this example we see the estimate for all respondents who finished Year 12 is 19 8 with an RSE of 2 63 The estimate for remote respondents who finished Year 12 is 42 1 with an RSE of 14 16 Both estimates have an RSE of less than 25 so are considered reliable however the estimate for remote respondents is much less reliable than the estimate for all respondents given that the RSE for remote respondents 14 16 is considerably higher than the RSE of all respondents 2 63 In addition we would not recommend using estimates obtained from respondents who have only completed Year 10 or Year 9 or below for rural respondents as the RSEs are higher tha
22. areas and minor topic areas are illustrated in figures 3 to 6 NCVER S Figure 3 Major topic area 1 Demographics Demographics Student Parent Country of birth Education Place of residence Gender Indigenous Date of birth age Occupation Socioeconomic status Country of birth Language spoken at home Socioeconomic status Figure 4 Major topic area 2 Education Education fee School transition Post school Post school plans School leavers Main activity Study Current study Past study Apprenticeships traineeships Current apprenticeships traineeships Past apprenticeships traineeships Deferred withdrew from study Changed institutions Changed course Changed left employer Changed stopped apprenticeship traineeship Satisfaction with study Careers advice Government payments and income Economic climate School characteristics Student characteristics Student achievement Time spent learning Perceptions about self and school Views on science Teaching and learning science Science career Views on the environment Use of computers Subjects courses Subjects courses VET School plans Careers advice Work experience Workplace learning TAFE Workplace learning VET Qualifications and results Government payments and income Economic climate LSAY 2006 cohort user guide Figure 5 Major topic area 3 Employment Employment Current Job history and training Seeking employment Not in the labour
23. by the media Taught to find information about post study jobs through education Taught to find information about post study jobs by friend acquaintances Taught to find information about post study jobs by recruitment employment 1 agencies Helped to develop formal plan 1 Helped to make career decision 1 Helped to make subject course decision Helped to prepare to apply for job 1 Helped to prepare post school study application Work experience Work experience 1 1 Work experience in year 9 or 10 1 1 Work experience undertaken 1 Number of days 1 1 Teaches what work is really like 1 1 E LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Teaches about people Teaches about instructions Teaches about thinking for self Teaches about confidence Teaches about job skills Teaches about work conditions Teaches about your future career 1 1 Workplace learning TAFE Workplace learning Number of days planned Number of days actual Teaches what work is really like Teaches about people Teaches about instructions Teaches about thinking for self Teaches about confidence Teaches about job skills Teaches about work conditions Teaches about your future career Workplace learning VET Workplace learning Workplace learning undertaken Number of days planned Number of days actual Number of day
24. force Employment characteristics Employment characteristics Looking for work Main activity Time worked Time worked Job search activity Education Wages and benefits Wages and benefits Problems looking for work Employment Starting work Job training Economic climate Aspirations Leaving work Leaving work Aspirations Working in a job while at school Working in a job post school Job training Job satisfaction Economic climate Perceptions about work Aspirations Figure 6 Major topic area 4 Social Social Health living arrangements and i General attitudes finance Leisure Life satisfaction Job aspirations Living arrangements Household possessions Children Marriage Aspirations Disability and health Volunteer Government payments Housing payments Finance Topic maps Topic maps have been developed for each of the 11 sub major topic areas The topic maps aim to improve accessibility of the LSAY data by linking common questions or variables within and between waves These common variables are identified as data elements Topic maps by sub major topic area can be found in the Topic maps section of this User guide A summary of the topic maps appears in table 3 NCVER a Table3 Topic maps Major topic area Topic map Sub major topic area Demographics Student Parent School Education School transition Post school Job history and training Seeking employment Not in the labour force
25. of Education ISCO International Standard Classification of Occupations ANZSCO Australian and New Zealand Standard Classification of Occupations ANZSIC Australian and New Zealand Standard Industrial Classification Education The International Standard Classification of Education ISCED 1997 is used to code parental education levels and expected student educational levels in the first wave of the 2006 cohort as part of PISA The ISCED has the following categories ISCED 1 primary education ISCED 2 lower secondary e g up to Year 10 ISCED 3B or 3C vocational pre vocational upper secondary e g Year 11 with Certificate III ISCED 3A upper secondary e g Year 12 ISCED 4 non tertiary post secondary e g certificate IV ISCED 5B vocational tertiary e g diploma ISCED 5A or 6 theoretically oriented tertiary and postgraduate e g bachelor degree postgraduate degree Further information about ISCED is available at lt http www uis unesco org ev php ID 3813 20161D2 DO TOPIC gt NCVER ss The Australian Standard Classification of Education ASCED is used to code the area of study from wave 2 2007 Occupation The International Standard Classification of Occupations ISCO 88 is used to code parental occupation and expected student occupation in the first wave of the 2006 cohort as part of PISA Further information about ISCO is available at lt http www ilo org public english bureau stat
26. random probability sampling the size of the sampling error for a given sample is measured using the standard error of the estimate It is important that users take into consideration the reliability of estimates obtained from survey data Standard errors confidence intervals and relative standard errors RSEs can be calculated to determine the reliability of the estimate s The greatest contributor to standard error is the sample size Small sample sizes generally result in higher standard errors and wider confidence intervals The RSE enables a comparison of the accuracy between two different estimates An estimate with a high RSE or wide confidence interval should be used with caution and users are advised against relying on estimates obtained from sample sizes of fewer than five or estimates that have an RSE of greater than 25 Standard errors The standard error of an estimate indicates the accuracy to which that estimate approximates the true population parameter There are multiple methods for calculating the standard errors in complex surveys One method commonly used is the Taylor series expansion This technique has been applied to obtain estimates of standard errors for the LSAY cohort reports These standard errors can then be used to calculate confidence intervals and relative standard errors Confidence intervals The confidence interval is an interval estimate of the population parameter Sample estimates which have high s
27. understand Finding out more about a new idea 1 Finding out how things work 1 Improving your skills after starting work 1 Learning new skills after starting work 1 Life satisfaction The work you do 1 1 1 1 1 What you do in your spare time 1 1 1 1 1 How you get on with people 1 1 1 1 1 The money you get each week 1 1 1 1 1 Your social life 1 1 1 1 1 Your independence 1 1 1 1 1 LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Your career prospects 1 1 1 1 1 Your future 1 1 1 1 1 Your life at home 1 1 1 1 1 Your standard of living 1 1 1 1 1 The way the country is run The state of the economy Job aspirations Where you live 1 1 1 1 Your life as a whole 1 1 1 1 Type of job expect at age 30 ISCO 1 Type of job expect at age 30 verbatim 1 Type of job expect at age 30 Science related Aspirations nfluence of family 1 nfluence of friends 1 nfluence of teachers 1 nfluence of media 1 nfluence of career advisors 1 nfluence of information from i employers nfluence of jobs work experience 1 Personal goal 1 Volunteer Canvassing campaigning fundraising 1 Unpaid member of board or committee Provide information Help organise activities Coaching teaching Collect serve or deliver food Provide health care support counselling Other Outcomes Job related skills Outcomes Helped get a job NCVER Wave Year
28. 09 5 2010 6 2011 Opportunities for training 1 1 1 1 1 Tasks assigned 1 1 1 1 1 Recognition 1 1 1 1 1 Opportunities for promotion 1 1 1 1 1 Economic climate Hours worked 1 1 Type of work 1 1 Changing of jobs 1 1 Study undertaken 1 1 Study plans 1 1 Perceptions about work Teaches what work is really like 1 1 Teaches about people 1 1 Teaches about instructions 1 1 Teaches about think for self 1 1 Teaches about confidence 1 1 Teaches about work conditions 1 1 Teaches about career you would like 1 1 Aspirations Wages 1 Freguency of pay 1 Would move to improve job opportunities Main reason would not move for job opportunities LSAY 2006 cohort user guide Topic map 7 Employment Job history and training Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Employment characteristics Work in job business farm at last interview Re definition of second job as main job Kind of work ANZSCO Kind of work Other second job ANZSCO Kind of work Other third job ANZSCO Employer s main kind of business ANZSIC Employer s main kind of business Other second job ANZSIC Employer s main kind of business Other third job ANZSIC Wages salary self employed Other second job Wages salary self employed Other third job Time worked Hours worked per week Other second job Hours worked per week Other third job Wages and benefits Pa
29. 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Month expect to complete study Year expect to complete study Current qualification level derived variable Full time or part time study status derived variable 1 1 1 1 1 1 Past study Study completed withdrawn deferred change d Main area of study Institution Full time or part time study First preference Month stopped study Year stopped study Highest qualification level completed derived variable Apprenticeships traineeships Still studying Confirmation of apprenticeship traineeship Qualification Main area of study Employer type Classes off the job training at TAFE Provider of off the job training Month started study Year started study Status in apprenticeship traineeship derived variable Current apprenticeships traineeships NCVER Employer type Classes off the job training at TAFE Provider of off the job training Full time or part time study Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Month expect to complete study 1 1 1 1 1 Year expect to complete study 1 1 1 1 1 Past apprenticeships Study completed withdrawn time i i i i i traineeships out other Employer type 1 1 1 1 1 Reason apprenticeship traineeship i i 1 i i ended Month stopped study 1 1 1 1 1 Year stopped study 1 1 1 1 1 Deferred withdrew from Reason Problems juggling
30. 2010 6 2011 First preference Reason did not take 1 1 1 1 1 up place other First preference Reason did not take i 1 i i i up place main reason University Offered place 1 1 1 1 1 University Institution 1 1 1 1 1 University Accepted place 1 1 1 1 1 University Reason did not take up i 1 i i i place taking break holiday travel University Reason did not take up i 1 i i i place required leaving home University Reason did not take up i 1 1 1 i place need Youth Allowance University Reason did not take up i 1 1 i i place considering options University Reason did not take up i 1 1 i 1 place course costs University Reason did not take up i 1 1 i 1 place financial University Reason did not take up i 1 1 i i place prefer to work University Reason did not take up i 1 1 i i place prefer to study at TAFE University Reason did not take up j 1 i 1 i place other University Reason did not take up 1 1 i i i place main reason Study status in bachelor degree or i i j j 7 i higher derived variable Study status in VET derived variable 1 1 1 1 1 1 In full time employment or full time i i 1 i 1 i education derived variable Current study Study type 1 1 1 1 1 Qualification 1 1 1 1 1 Main area of study 1 1 1 1 1 Institution 3 5 5 5 10 Full time or part time study 3 4 4 4 4 Month started study 1 2 2 2 2 Year started study 1 2 2 2 2 LSAY 2006 cohort user guide Minor topic area Data element 1 2006
31. 4170 9 353 8 380 7 299 6 316 5 420 of wave 1 100 66 0 59 1 51 5 44 6 38 2 of previous wave na 66 0 89 6 87 1 86 5 85 8 Sources of error Estimates based on sample surveys have two major sources of error non sampling and sampling error A brief description of the two types and an outline of what can be done to overcome the effects of these errors are given below ae LSAY 2006 cohort user guide Non sampling error Non sampling error arises from inaccuracies in collecting recording and processing the data Some common examples of non sampling error include non response incorrect responses missing responses and interviewer and processing error Non sampling error can be accounted for in part by using weighted estimates to adjust for non response However there are no statistical measures to accurately adjust for other types of non sampling error Nevertheless other types of non sampling error can be minimised through good questionnaire design training and monitoring of interviewers the use of computer assisted interviews and effective data checking and processing procedures Non response All surveys suffer from error related to non response Non response is a form of non sampling error that can be taken into account in the analysis of survey data There are typically two forms of survey non response Item non response occurs when a respondent does not answer all the questions in the survey Unit non response occurs wh
32. 6 Institution 36 Topic maps 37 Topic map 1 Demographics Student 39 Topic map 2 Demographics Parent 40 Topic map 3 Education School 42 Topic map 4 Education School transition 53 Topic map 5 Education Post school 55 Topic map 6 Employment Current 63 Topic map 7 Employment Job history and training 67 Topic map 8 Employment Seeking employment 69 Topic map 9 Employment Not in the labour force 71 Topic map 10 Social Health living arrangements and finance 72 Topic map 11 Social General attitudes 76 Appendix A Updates to the Y06 data file 82 LSAY 2006 cohort user guide Tables and figures Tables 1 NO O NO U A V N o 1 12 13 Technical documents PISA technical documents Topic maps User guide data element documents Summary of PISA variable naming conventions Summary of LSAY non standard variable naming conventions Derived variables Sample sizes and response rates LSAY Y06 Weight variables Estimates standard errors RSEs and confidence limits for highest school level completed Y06 cohort in 2008 for a large sample all respondents Estimates standard errors RSEs and confidence limits for highest school level completed Y06 cohort in 2008 for a small sample remote respondents Summary of classifications and code frames used in the LSAY Y06 dataset Summary of changes made to the Y06 datasets Figures 1 NO ON O uo A U N Cohort reports LSAY hierarchical l
33. Australian National University the University of Melbourne the University of Queensland the University of Technology Sydney and the University of Western Australia the National Centre for Vocational Education Research NCVER and the Commonwealth of Australia shall not be held liable for any breach of this undertaking LSAY student achievement information cannot be reported at the school sector aggregate for the LSAY 2003 and 2006 cohorts Where research findings based on LSAY are published or otherwise placed in the public arena the user must agree to provide the Australian Data Archive and the National Centre for Vocational Education Research with the bibliographic details and where available online links to any published work including journal articles books or book chapters conference presentations theses or any other publications or outputs based wholly or in part on the material Overview of the questionnaires Programme for International Student Assessment PISA The first wave of the LSAY Y06 cohort was incorporated into the OECD s Programme for International Student Assessment as was the case with the LSAY Y03 cohort It is therefore important to understand the PISA 2006 dataset when using the LSAY Y06 cohort data The following section briefly describes some of the nuances of the PISA dataset but users are also encouraged to read the PISA technical documents as outlined in table 2 As part of PISA 2006 students w
34. COBN F All COBN_S All LANGN All CNTFAC_N All CNTFAC_E All CNTFAC PISA variable removed replaced with CNTFAC_E All PISA weights added to dataset WTYYGEN P All ACHYYWT_P All WTYYYY_P All Minor amendments made to methodology used to calculate 2007 and 2008 weights WT07GEN 9353 ACH07WT 9353 WT2007 9353 WT08GEN 8380 ACHO8WT 8380 WT2008 8380 Minor amendments made to calculation of some derived variables XCEL2007 5 XCEL2008 29 XHEL2008 4 XFTS2008 10 XBAC2007 5 XBAC2008 23 XVET2007 7 XVET2008 229 XEMP2007 312 XEMP2008 163 Corrected Don t know formats for postcode variables Wave year Version Date published Variable Variable Description Number of name observations affected PC2007 165 PC2008 2 Waves 1 to 3 Version 2 Derived variables added to dataset see section on Derived variables 2006 to 2008 2007 and 2008 weights added to dataset WT07GEN 9353 ACHO7WT 9353 WT2007 9353 WTO8GEN 8380 ACHO8WT 8380 WT2008 8380 LBH003B Variable LBH003B corrected as was duplicate of LBH003C 3093 2 2007 Version 1 New data file containing data from waves 1 2006 and 2 2007 All ongitudinal urveys of Australian Youth Australian Government 9 Department of Education Employment and Workplace Relations National Centre for Vocational Education Research Ltd Level 1 33 King William Street Adelaide South Australia PO Box 8288 Station Arcade SA 5000 Australia Telephone 61 8 8230 8400
35. FTS2007 Changes to Full time or part time study status due to correction made to Current study status to qualification level XFTS2010 XFTS2007 3 XFTS2008 5 XFTS2009 12 XFTS2010 15 Study status in bachelor XBAC2008 One respondent who had indicated in a previous interview that they had commenced 1 degree or higher study in a bachelor degree or higher level gualification but did not confirm that course of study in the current interview was derived as having commenced but not completed study in a bachelor degree or higher level gualification This derivation has been modified so that this respondent is now derived as having never commenced a bachelor degree or higher level gualification XBAC2009 Change to Study status in bachelor degree or higher due to correction made to Study 1 status in bachelor degree or higher from previous year XBAC2010 Some respondents who had indicated in a previous interview that they had commenced 3 study in a bachelor degree or higher level gualification but did not confirm that course of study in the current interview were derived as having commenced but not completed study in a bachelor degree or higher level gualification This derivation has been modified and is now derived as having never commenced a bachelor degree or higher level qualification Wave year Version Date published Variable Variable name Description Number of observations affected Study status in VET XVET2007 XVET2008
36. Facsimile 61 8 8212 3436 Website www ncveredu au Email ncver ncveredu au
37. School teachers nfluence Media fluence Career advisors fluence Information from employers fluence Jobs school work experience 1 1 School leavers NCVER Left school before completing Year 12 Month left school Year left school Year level left school Feelings about having left school Main activity Prepared to make decisions about future career Reason Have job apprenticeship Reason To get job apprenticeship Reason Not good at school Reason Study training not available Reason Didn t like school Reason Financially difficult Reason Teachers Reason Earn own money Reason Parents Minor topic area Data element Wave Year 4 2009 5 2010 6 2011 Reason Subjects courses not Main activity 1 available at school Reason Year 12 wouldn t help get a i i i job Reason Year 12 wouldn t help with 1 1 1 further study training Reason Main reason 1 1 1 Received study training advice i i i University Received study training advice TAFE 1 1 1 Received study training advice Other i i i educational organisation Received study training advice None 1 1 Study training advice On campus 1 i university Study training advice On campus j i i TAFE Study training advice On campus i i i other Study training advice Mentoring 1 1 1 Study training advice Summer i i i school short course Study training advice Staff student visit 1 1 1 Study tr
38. TECHNICAL REPORT 55 Surveys of i ra i Longitudinal Australian Youth Longitudinal Surveys of Australian Youth Longitudinal Surveys of Australian Youth LSAY 2006 cohort user guide National Centre for Vocational Education Research LONGITUDINAL SURVEYS OF AUSTRALIAN YOUTH TECHNICAL REPORT 55 Date created January 2010 Last updated March 2013 Version 3 0 The views and opinions expressed in this document are those of NCVER and do not necessarily reflect the views of the Australian Government or state and territory governments Publishers note Additional information relating to this publication is available from NCVER s website lt http www lsay edu au publications 2258 html gt Commonwealth of Australia 2013 With the exception of the Commonwealth Coat of Arms the Department s logo any material protected by a trade mark and where otherwise noted all material presented in this document is provided under a Creative Commons Attribution 3 0 Australia lt http creativecommons org licenses by 3 0 au gt licence The details of the relevant licence conditions are available on the Creative Commons website accessible using the links provided as is the full legal code for the CC BY 3 0 AU licence lt http creativecommons org licenses by 3 0 legalcode gt The Creative Commons licence conditions do not apply to all logos graphic design artwork and photographs Reguests and enguiries concerning
39. acters followed by the two INTSASO9 characters WI and then D for day of interview M for month of interview or Y for year of interview The INTDAT and INTSAS variables are the consolidated interview date variables in both character and SAS date format respectively followed by two digits for the survey year Postcode PC2008 Respondents home postcodes are indicated by the first two PC2009 characters PC followed by the year of interview NCVER Non standard Examples of non Description variable standard variable names Sample and derived LBWSAM01 Sample and derived items look at information from surveys of items LDWSAM07 previous years They have been created to enable more efficient LDWDVO1 and effective direction of guestions For example the variable LDWSAM07 looks at whether the respondent had a job at the previous interview Questions about whether respondents have the same job as reported at their last interview would only be asked of those who were recorded as being employed at the previous interview Sample items are denoted by the first character L to indicate the LSAY survey instrument was used followed by the wave identifier A to F followed by the character W followed by the characters SAM or DV for items derived by the field contractor followed by two digits denoting the sample derived item Weights WTO9GEN Weight variables are denoted by
40. acy How Australia measures up The role of plausible values in large scale surveys lt https mypisa acer edu au images mypisadoc plausiblevaluesins ee pdf gt How do I use plausible values Unbiased estimates of achievement will only be obtained if plausible values are incorporated appropriately The following are some key points Averaging plausible values over individuals will lead to biased estimates and incorrect standard errors Analysis should be repeated for each plausible value five times and any subsequent estimate for example coefficients and or standard errors combined in an appropriate way to obtain population estimates Plausible values are correlated within a domain and as such an analysis may be undertaken using only a single plausible value but being aware that standard errors may be incorrect Users are reminded that plausible values are not equivalent to the achievement scores in the Y95 and Y98 LSAY cohorts nor are they equivalent to an individual s raw test scores nev The LSAY guestionnaires From 2007 wave 2 students have been contacted annually by telephone and asked a range of questions across the following sections Section A School Section B Transition from school Section C Post school study Section D Work Section E Job history Section F Job search activity Section G Not in the labour force Section H Living arrangements finance and health
41. aining advice Youth Allowance 1 1 1 Main reason returned to school 1 1 1 Main activity 1 1 1 LSAY 2006 cohort user guide Topic map 5 Education Post school Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Study NCVER Study status at last interview Still studying Confirmation of study Confirmation of deferred study Resumption of deferred study Commenced study Study type Qualification Qualification at last interview Main area of study Institution Month started study Year started study Applied for university place Intend to apply for university place Intend to reapply for university place First preference Offered place First preference Institution First preference Accepted place First preference Reason did not take up place taking break holiday travel First preference Reason did not take up place required leaving home First preference Reason did not take up place need Youth Allowance First preference Reason did not take up place considering options First preference Reason did not take up place course costs First preference Reason did not take up place financial First preference Reason did not take up place prefer to work First preference Reason did not take up place prefer to study at TAFE 1 1 Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5
42. archive where the data file is made available through the Australian Data Archive by another archive declares that those who carried out the original analysis and collection of the data bear no responsibility for the further analysis or interpretation of them 4 Use of the material is solely at the user s risk and the user must indemnify the Australian Data Archive and the ADA consortium members the Australian National University the University of Melbourne the University of Queensland the University of Technology Sydney and the University of Western Australia the National Centre for Vocational Education Research NCVER and the Commonwealth of Australia against any liability loss or expense incurred by the ANU ADA NCVER or Commonwealth arising from any action taken against LSAY 2006 cohort user guide NCVER them resulting from unauthorised use or duplication of material or any other breach of conditions set out in this undertaking The Australian National University the Australian Data Archive the National Centre for Vocational Education Research and the Commonwealth of Australia shall not be held responsible for the accuracy and completeness of the material supplied Where applicable a the user must draw the terms and conditions of the undertaking to the attention of persons within the department organisation who shall make use of the material b the Australian Data Archive and the ADA consortium members the
43. articularly useful for cross validation for data users See figure 1 for an illustration of the cohort reports Figure 1 Cohort reports o one Longitudinal al Surveys of Australian Youth Longitudinal Surveys of Australian Youth Y06 cohort to 2008 released March 2009 Table 2 Education Indicators for Y06 LSAY cohort 2006 2008 Year 2006 2007 2008 Wave 1 2 3 Average age of respondents at 30 June s ier ay years Number of respondents 14170 9353 8380 Attending school Year 12 01 184 55 3 Year 11 19 8 57 3 8 1 Year 10 70 8 87 0 2 Year 9 or below 93 0 2 0 0 At Scho Year level unknown 0 0 0 0 0 0 Not at school 0 0 15 5 364 Level of current study study leading to a gualification Certificate 0 0 11 12 Certificate II 0 0 08 0 8 Other technical papers Other technical papers that may be useful include sampling and weighting methodology and the PISA technical reports data analysis manuals and country reports NCVER O Technical paper number 61 Weighting the LSAY PISA cohorts can be accessed at lt http www lsay edu au publications 2429 html gt The PISA 2006 technical report data analysis manuals and country report provide all the information reguired to understand the PISA 2006 data contained in the first wave of the Y06 cohort and to perform analyses in accordance with the complex methodologies used to collect and process the data The PISA 2006 technical report is available from
44. as been integrated with the Organisation for Economic Co operation and Development OECD Programme for International Student Assessment PISA The LSAY research program provides a rich source of information to enable a better understanding of young people and their transitions from school to post school destinations it also explores their social outcomes such as wellbeing Information collected as part of the LSAY program covers a wide range of school and post school topics including student achievement student aspirations school retention social background attitudes to school work experiences and what students do when they leave school LSAY is managed and funded by the Australian Government Department of Education Employment and Workplace Relations DEEWR with support from state and territory governments On 1 July 2007 the National Centre for Vocational Education Research NCVER was contracted to provide LSAY analytical and reporting services NCVER is undertaking this service for the department in collaboration with the Australian National University s Social Policy Evaluation Analysis and Research Centre SPEAR Between 1995 and 2007 the LSAY analytical and reporting services were provided by the Australian Council for Educational Research ACER jointly with the Department of Education Science and Training DEST More information can be obtained from the LSAY website or by contacting the LSAY team at NCVER Toll free
45. bles in the Y06 dataset as well as basic information about each variable Data can be filtered and inspected by wave year questionnaire section topic area s and or data element See the section The LSAY data sub section Variable listing metadata workbook for further information The metadata workbook can be accessed at lt www lsay edu au publications 2258 html gt under the supporting documents tab If you have any feedback or issues finding the information you need in this guide please do not hesitate to contact the LSAY branch at NCVER Toll free 1800 825 233 Email lt lsay ncver edu au gt Telephone 61 8 8230 8400 Website lt www lsay edu au gt Facsimile 61 8 8212 3436 Registration You need to register for the LSAY website to access LSAY resources and materials Registration is free and gives you web access to LSAY cohort reports technical documents and questionnaires web access to the full text of LSAY research reports and briefing papers email alerts to keep you informed about the latest research and data releases from LSAY The following link can be used to register for the LSAY website lt http www lsay edu au subscribe html gt Further information about registering for the LSAY website can be found at lt http www say edu au newsevents subscribe html gt NCVER ot The Y06 cohort In 2006 a nationally representative sample of 14 170 students aged 15 years was selected
46. ce personal value index 1 Teaching and learning SETE 1 science Course Biology 4 Course Physics 4 Course Chemistry 4 Teaching and learning 17 Motivation 5 Self concept 6 Teaching and learning Applications i index Teaching and learning Hands on index Teaching and learning Interaction i index Teaching and learning Investigations i index Motivation index 1 Self concept index 1 Science career Usefulness 4 Knowledge 4 Future 4 Knowledge index 1 Usefulness index 1 Future index 1 Views on the environment Informed 5 nformation source Air pollution 6 nformation source Energy shortages 6 nformation source Extinction 6 nformation source Forest clearing 6 nformation source Water shortages 6 nformation source Nuclear waste 6 Concern 6 LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Future Responsibility Informed index Concern index Future index Responsibility index Use of computers Used computer How long used computers Use computer at home Use computer at school Use computer other places Frequency How well Frequency Internet entertainment use index Frequency Programs software use index How well High level tasks index How well Internet tasks index Subjects courses NCVER English English subject LOTE LOTE subject Maths Maths subject Science Scie
47. cohort user guide formats and base populations for the Y06 dataset From wave 4 the Y06 guestionnaires and freguency tables will be available from the same location but information usually contained in the code books will be updated to this User guide and its supporting documents Table 1 provides a summary of the LSAY Y06 technical documents Table 1 Technical documents Wave year Technical report paper Wave 1 2006 Technical report no 42p Preliminary codebook Technical report no 46 Wave 2 2007 Technical report no 47 Wave 3 2008 Technical report no 52 Wave 4 2009 Technical paper no 56 Wave 5 2010 Technical paper no 62 Wave 6 2011 Technical paper no 75 Note All 2006 PISA questionnaires are available from the OECD website lt http pisa2006 acer edu au downloads php gt Cohort reports The Y06 cohort reports provide a longitudinal snapshot of the activities of the Y06 cohort from 2006 to the latest survey wave They are updated annually as new waves of data become available The content of the cohort reports focuses on the areas of educational attainment employment measures of engagement in study and work and social outcomes The cohort reports present a series of tables for each of the indicators Each series of tables can be filtered by a range of demographic variables and be downloaded into Excel The Y06 cohort reports can be accessed at lt http www lsay edu au cohort 2006 101 html gt and are p
48. e B iu ad 48 33 Conditional Format Cell Da Sot amp Find amp u 00 34 p S g Formatting as Table Styles Z Format lt 2 Filter Select Clipboard Font E Alignment E Number Ta Styles Cells Editing v fe Minor B C D G H I J K Section Major Sub major Data element Variable Type Label Question Base E CA 2 Education Post schoof Study Study type LBCA002 Num CA2Typeofstudyortrai would like you to think back to the f Study or training since leav c 2 Education Post schoof Current study Study type LBC082 Num CB2Currentstudyortra Are you currently doing READ OU No current study or training CA 2 Education Post schoofStudy Study type LCCA00B Num _CAB Type of study or trai What was the first study or training Study or training since leav c 2 Education Post schoofCurrent study Study type LCCOB2 Num C82 Current study or tra Are you currently doing READ OU No current study or training cA 2 Education Post schoof Study Study type LDCA008 Num _CAB Type of study or trai What was the first study or training Study or training since leav c 2 Education Post schoofCurrent study Stu LDC082 Num C82 Current study or tra Are you currently doing READ OU No current study or training 3008 M 4 M Variables Formats J 4 Ready 6 of 2982 records found To identify variables for analysis and to promote accurate variable selection refer to the topic maps contained in the Topic maps
49. e first worksheet Variables includes the variable type variable label question wording and base population The second worksheet Values lists each variable and the values that variable can take where applicable Variable selection Not all variables assigned to a data element are directly comparable Additional attributes such as question wording values classifications used and base populations must be considered when selecting variables and analysing the data Data elements have been created to assist in grouping thereby simplifying variable selection They are unique within a minor topic area but may not be unique across topic areas For example the data element Study type exists under the major and sub major topic area Education Post school This data element appears under two different minor topic areas Study and Current study The Study minor topic area may include both past and current study depending on the questionnaire sequencing When identifying a data element and or variable for use it is important to consider other related data elements that may be located in a different topic area This is illustrated in figure 7 using an excerpt from the metadata workbook NCVER a Figure 7 Identifying related topic areas S Home Insert Page Layout Formulas Data Review View DM mx lt E i bh 1 Inset E B calibri js JA a General x E ERA Ey 3 27 FB EF 2 a Z Delete a Past
50. e subject only unknown or some other qualification than those listed were previously derived as not studying for a qualification The derivation has been modified so that these respondents are now derived as undertaking a certificate at an unknown qualification level Some respondents who had changed course and were undertaking a bachelor degree or higher level qualification were incorrectly derived as studying for a graduate diploma or graduate certificate These records are now derived as currently studying for a bachelor degree or higher level qualification Wave year Version Date published Variable Variable Description Number of name observations affected XCEL2010 Changes to Current qualification level due to correction made to Current qualification 56 level in previous year Respondents who were undertaking an apprentice traineeship and whose qualification type was a short course or recreational course single module subject only unknown or some other qualification than those listed were previously derived as not studying for a qualification The derivation has been modified so that these respondents are now derived as undertaking a certificate at an unknown qualification level Highest qualification XHEL2008 Change to Highest qualification level completed due to correction made to Current level completed to qualification level in previous year XHEL2010 XHEL2008 i XHEL2009 1 XHEL2010 1 Full time or part time X
51. ed and unweighted The Y06 cohort reports can be accessed at lt http www lsay edu au cohort 2006 101 html gt Researchers are encouraged to determine their own weighting or analysis methodology to counteract attrition this may include using methods of multiple imputations for missing values Table 9 shows the three different types of available weights and the variable naming convention for each where YY or YYYY denotes the survey year at two or four digits respectively Weights that sum to the population size are denoted by _P at the end of the weight variable Table 9 Weight variables Weight Variables Sum Sample weight WTYYGEN Sample size in YY Sample weight N WTYYGEN_P Population size 234 940 Attrition weight ACHYYWT Sample size in YY Attrition weight N ACHYYWT_P Population size 234 940 Final weight WTYYYY Sample size in YYYY Final weight N WTYYYY_P Population size 234 940 LSAY 2006 cohort user guide Sampling error Users of the LSAY data must consider the size of the sampling error when deriving or interpreting estimates obtained from LSAY Sampling error arises because estimates are obtained from the use of a sample rather than from measuring the entire population It is possible to select many different individual samples from a single population each of these would provide a different population estimate An estimate obtained from a sample is subject to sample to sample variation sampling error In
52. egan job 1 1 1 1 1 Year began job 1 1 1 1 1 How found job 1 1 1 1 1 Looking for work Prefer full time or part time work 1 1 1 1 1 Looking for full time work 1 1 1 1 1 Looking for work 1 1 1 1 1 Looking for work additional or to i 1 i 1 i change jobs Working i a Job wnile at Kind of work want as career 1 school Learnt about careers LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Enjoy work 1 Family needs money 1 Independence 1 Help get job 1 Family business 1 Support myself 1 Spending money 1 Working in a job post Full time job since leaving school school Full time job since leaving full time 1 1 1 i study Time taken to find full time job 1 1 1 1 Still have job 1 1 1 1 Job training Classroom based training 1 1 1 1 Hours of classroom based training Training outside workplace Hours of training outside workplace On the job training T rise aining helped get promotion or pay T pay rise aining could help to get promotion or T responsibility aining could help to get more Training could help to get a different type of job Use of training Suitable amount of training received Job satisfaction NCVER Like job as career Kind of work Utilise skills experience Immediate boss supervisor Other people Pay Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 20
53. en not all respondents answer the survey due to for example refusal to participate or inaccurate contact details Item non response can be minimised with the use of CATI which can forward feed information from previous interviews Item non response is generally treated using imputations There are currently no imputed data for missing values in LSAY However data users can apply a number of techniques to help make the data more complete The use of statistical modelling techniques such as Multiple Imputation MI allows data users to estimate item non response along with their respective standard errors Unit non response also called attrition can lead to biased population estimates and incorrect standard errors particularly if certain groups of the sample drop out at differing rates Survey attrition is counteracted by attempting to maximise the year on year response rate appropriate statistical modelling techniques and or the application of appropriate survey weights Weights In order for the LSAY sample to more accurately represent the population of Australian 15 year olds in 2006 the collected sample must be weighted to account for differences in the sampling distributions from the original population distribution that may have arisen during the sampling process In 2010 NCVER reviewed the weighting methodology used for the Y03 cohort As a result of this review a logistic regression approach to weighting has been adopted This m
54. ere assessed in mathematical literacy reading literacy and scientific literacy to provide information on school achievement Students also completed a background questionnaire about their families their views on a range of science related issues the environment educational and vocational plans attitudes to school and learning work experience workplace learning and part time work School principals were also asked to complete a questionnaire about their schools PISA 2006 covered three domains reading literacy mathematical literacy and scientific literacy For each PISA data collection one of these domains is chosen as a major domain while the others are considered minor domains A major domain is tested more thoroughly in the year of collection The major domain for PISA 2006 was scientific literacy The PISA 2006 assessments consisted of a self completion written test Examples of items from the PISA 2006 assessment are available in Assessing scientific reading and mathematical literacy a framework for PISA 2006 available at lt http www oecd org document 33 0 3343 en 32252351 32236191 37462369 1 1 1 1 00 html gt This publication presents the guiding principles of the PISA 2006 assessment which are described in terms of the content that students need to acguire the processes that need to be performed and the context in which knowledge and skills are applied It also illustrates the assessment domains with a range of simple tasks
55. ethodology is consistent with the approach taken to calculate the Y06 weights These weights are provided in the datasets deposited with the ADA alongside the previous version of the weights denoted by an _X at the end of the weight variable name Further detailed information regarding the current weighting methodology used is available from technical paper number 61 Weighting the LSAY PISA cohorts which can be accessed at lt http www lsay edu au publications 2429 html gt NCVER a There are two weighting procedures applied to the LSAY data 1 Sample weights reflect the original sample design and ensure that the sample matches the population distribution from which the original sample was drawn In the Y06 cohort two sampling weights have been created The first weights sum to the sample size for that given wave For example the sample weights add to 14 170 in wave 1 9353 in wave 2 etc In the second set of weights the sum of the weights equals the original population from which the sample was drawn 234 940 Students from states and territories with smaller numbers of 15 year olds are over sampled and students from jurisdictions with larger numbers of 15 year olds are under sampled In order for the sample to more accurately represent the population of Australian 15 year olds the sample is weighted so that sample sizes within strata are proportional to the original population sizes of the states and territories that is s
56. evels Major topic area 1 Demographics Major topic area 2 Education Major topic area 3 Employment Major topic area 4 Social Identifying related topic areas PISA variable naming convention LSAY standard variable naming convention NCVER 11 17 22 23 26 27 29 30 32 34 34 35 82 11 19 20 20 21 21 24 25 27 Background The Longitudinal Surveys of Australian Youth LSAY is a research program that tracks young people as they move from school into further study work and other destinations It uses large nationally representative samples of young people to collect information about education and training work and social development It includes surveys conducted from the mid 1970s through to the mid 1990s the Youth in Transition YIT program the Australian Longitudinal Survey ALS the Australian Youth Survey AYS and the current LSAY collection which began in 1995 Survey participants in the current LSAY collection collectively known as a cohort enter the study at age 15 years or as was the case in earlier studies when they were in Year 9 Individuals are contacted once a year for up to 12 years but respondents can miss one survey wave and still remain in the survey Studies began in 1995 Y95 cohort 1998 Y98 cohort 2003 Y03 cohort 2006 Y06 cohort and more recently in 2009 Y09 cohort About 14 000 students start out in each cohort Since 2003 the initial survey wave h
57. her 1 1 1 Husband wife partner currently working 1 1 1 Husband wife partner other activity 1 1 1 Husband wife partner works full time or i f i part time Husband wife partner current i i occupation ANZSCO Living with parent s derived variable 1 1 1 1 1 1 Living in own home derived variable 1 1 1 1 1 1 Number of dependent children derived 1 i 1 i i i variable Household possessions Desk 1 Own room 1 Quiet study place 1 Computer 1 Software 1 Internet 1 Calculator 1 LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Literature Poetry Art Textbooks Dictionary Dishwasher DVD VCR Cable pay TV Digital camera Plasma TV Number of mobile phones Number of TVs Number of computers Number of cars Number of books 1 Children Number of children Age of child 1 Age of child 2 Age of child 3 Age of child 4 Age of child 5 Child ren are step child ren fostered Marriage Marital status Marital status at last interview Month married Year married Lived together before marriage Month started to live together Year started to live together Marital status derived variable Disability and health NCVER General health Disability health problem limits amount or type of work Minor topic area Data element Wave Year 3 2008 4 2009 5 2010 6 2011 Disability health proble
58. igher Study status in VET XVET Completed Year 12 or X122 certificate II or above Completed Year 12 or X123 certificate III or above Labour force status XLFS Full time or part time XFTP employment status Permanent or casual XEMP employment Status in XATR apprentice traineeship Job mobility during last XMOB year Average weekly pay XWKP Average hourly pay XHRP Average weekly hours XHRS worked Occupation 1 digit XOCC ANZSCO first edition In full time employment XFTE or dull time education Wave year Version Date published Variable Variable Description Number of name observations affected Any spell of XUNE unemployment during the year Marital status XMAR Living with parent s XATH Living in own home XOWN Number of dependent XCHI children Minor modifications made to some derived variables Highest school level XHSL2009 3 completed Study status in VET XVET2009 25 Completed Year 12 or X1222009 1 certificate II or above Completed Year 12 or X1232009 1 certificate III or above Permanent or casual XEMP2006 1203 employment Average weekly pay XWKP2006 338 XWKP2007 593 XWKP2008 562 XWKP2009 3052 Average hourly pay XHRP2009 2400 Waves 1 to 4 Version3 10 September PISA variables added 2006 to 2009 2010 SCHOOLID All STIDSTD All STUDENTID All SRC_M All SRC_F All SRC_E All SRC_S All COBN_M All Wave year Version Date published Variable Variable Description Number of name observations affected
59. ills after starting work 1 Learning new skills after starting work 1 Life satisfaction The work you do 1 1 1 1 1 What you do in your spare time 1 1 1 1 1 How you get on with people 1 1 1 1 1 The money you get each week 1 1 1 1 1 Your social life 1 1 1 1 1 Your independence 1 1 1 1 1 Your career prospects 1 1 1 1 1 Your future 1 1 1 1 1 Your life at home 1 1 1 1 1 LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Your standard of living 1 1 1 1 1 The way the country is run 1 1 The state of the economy 1 1 Where you live 1 1 1 1 1 Your life as a whole 1 1 1 1 1 Job aspirations Type of job expect at age 30 ISCO 1 Type of job expect at age 30 verbatim 1 Type of job expect at age 30 Science related Aspirations fluence of family 1 nfluence of friends 1 nfluence of teachers 1 nfluence of media 1 nfluence of career advisors 1 nfluence of information from employers fluence of jobs work experience 1 Personal goal 1 1 Volunteer Canvassing campaigning fundraising 1 Unpaid member of board or committee 1 Provide information 1 Help organise activities 1 Coaching teaching 1 Collect serve or deliver food 1 Provide health care support counselling Other 1 Outcomes Job related skills 1 Outcomes Helped get a job 1 NCVER Appendix A Updates to the Y06 data file The following table tracks updates made to the Y06 da
60. ion session 1 1 1 TAFE information session 1 1 1 Careers expo fair 1 1 1 Used internet site computer program 1 1 1 Group discussion 1 1 1 Other careers advice 1 Most useful careers advice 1 1 1 Talked with family 1 1 Talked with friends 1 1 Usefulness Talked to careers i i i guidance officer Usefulness Talked with person in i i i desired job Usefulness Questionnaire 1 1 1 Usefulness Read information 1 1 1 Usefulness Visited workplace 1 1 1 Usefulness University information 4 i i session Usefulness TAFE information session 1 1 1 Usefulness Attended careers expo fair 1 1 1 Usefulness Used internet i i i site computer program Usefulness Group discussion 1 1 1 Usefulness Other careers advice 1 Usefulness Talked with family 1 1 Usefulness Talked with friends 1 1 Taught to develop formal study plan 1 1 1 Taught to develop formal study plan at i 1 1 NCVER school Taught to develop formal study plan by family Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Taught to develop formal study plan by myself Taught to develop formal study plan by career expos advisors Taught to develop formal study plan by other source Taught to develop formal study plan by social community workers Taught to develop formal study plan by the Job Guide Taught to develop formal study plan by the media Taught to develop formal study plan through education
61. isco isco88 index htm gt The Australian and New Zealand Standard Classification of Occupations ANZSCO first edition is used to code the remaining occupational data from waves 1 to 4 2006 09 This includes the national options questions asked at wave 1 as part of PISA Industry The Australian and New Zealand Standard Industrial Classification ANZSIC 2006 is used to code industries for all waves of the 2006 cohort Institution Non standard institution code frames have been developed specifically for LSAY to enable consistent coding of education institutions The code frame incorporates information about the institution campus and uses six digits to code institutions including campus from wave 2 2007 The institution code frames can be accessed at lt www say edu au publications 2258 html gt 4 ABS Australian Bureau of Statistics Australian Standard Classification of Education ASCED cat no 1272 0 Canberra 2001 5 ABS Australian and New Zealand Standard Classification of Occupations 1st edn cat no 1220 0 ABS 2006 ABS Australian and New Zealand Standard Industrial Classification cat no 1292 0 Canberra 2006 86 LSAY 2006 cohort user guide Topic maps The following series of topic maps list the data elements for each sub major topic area by minor topic area The digits within the tables indicate the survey waves in which this data element exists number of times the data element ap
62. k depending on the young person s circumstances Due to both population shifts over time and survey attrition care needs to be taken when comparing individual waves of the cohort with other samples drawn from different populations For example it can be misleading to compare the LSAY Y06 wave 3 2008 information with information about 17 year olds from other surveys in the same year Prior to the development of this User guide technical papers including the questionnaire frequency tables and code books contained information about the Y06 cohort Information from the technical papers has been consolidated in this User guide to provide a single source for Y06 technical information These documents are discussed below Technical documents questionnaires frequency tables and code books The following four questionnaire instruments were used in PISA 2006 the school questionnaire the student questionnaire the parent questionnaire the information communication technology questionnaire The parent and information communication technology questionnaires were offered as national options The 2006 PISA questionnaires and code books are available from the OECD PISA website lt http pisa2006 acer edu au downloads php gt The LSAY technical documents include guestionnaires freguency tables and code books and can be accessed at lt www lsay edu au data 31271 html gt The code books include the variable names LSAY 2006
63. me education and time or part time study status XFTE2009 XFTE2007 1 XFTE2009 1 Waves 1 to 5 Version 4 December 2011 Wave 8 2010 variables added to dataset 2006 to 2010 Variables renamed to maintain consistency with standard variable naming convention Number of VET subjects A24SUM A24SUM renamed to LBA024SU School state LCB015 LCB015 renamed to LCB015A Awarded certificate SCHLSTAT SCHLSTAT renamed to LCB015 Result B19SCORE B19SCORE renamed to LCB019S Minor corrections made to some derived variables Current qualification XCEL2008 Some respondents who were continuing their apprenticeship traineeship from the 207 level previous year were incorrectly assigned as not doing a qualification rather than currently undertaking a certificate Wave year Version Date published Variable Variable Description Number of name observations affected XCEL2009 362 Highest qualification XHEL2009 Changes to Highest qualification level due to correction made to Current qualification 13 level level in previous year Study status in VET XVET2008 Changes to Study status in VET due to correction made to Current qualification level 204 XVET2009 Changes to Study status in VET due to correction made to Current qualification level 363 and Highest qualification level Full time or part time XFTS2008 Changes to Full time or part time study status due to correction made to Current 207 study status qualificati
64. ms arms legs hands Disability health problems sight Disability health problems hearing Disability health problems skin allergies Disability health problems breathing asthma bronchitis Disability health problems heart blood pressure Disability health problems stomach liver kidney digestive problems Disability health problems diabetes Disability health problems depression bad nerves Disability health problems epilepsy Disability health problems dyslexia other learning problems Disability health problems Chronic fatigue post viral syndromes Disability health problems other problems or disabilities You felt nervous You felt hopeless You felt restless or fidgety You felt that everything was an effort You felt so sad that nothing would cheer you up You felt worthless Government payments Youth Allowance Newstart Allowance Parenting Payment Sickness Allowance Disability Support Pension Family Tax Benefit Other None of these 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 LSAY 2006 cohort user guide Minor topic area Wave Year Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Amount per fortnight received in 1 1 1 1 government payments Amount per year received in 1 government payments Housing payments Freguency of housing payments 1 1 Amount of housing payments 1 1 Finance Use of credit card Freguenc
65. n 1 1 Age discrimination 1 1 Other discrimination 1 1 Economic climate Job prospects 1 1 Study plans 1 1 Aspirations Wages 1 Frequency of pay 1 Would move to improve job Opportunities Main reason would not move for job opportunities LSAY 2006 cohort user guide Topic map 9 Employment Not in the labour force Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Main Activity Main Activity 1 1 1 1 1 Education Likelihood of beginning full time study 1 1 1 1 1 Timeframe for beginning study 1 1 1 1 1 Employment Likelihood of seeking employment 1 1 1 1 1 Timeframe for seeking employment 1 1 1 1 1 Aspirations Wages 1 Frequency of pay 1 Would move to improve job opportunities Main reason would not move for job opportunities NCVER Topic map 10 Social Health living arrangements and finance Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Living arrangements Type of accommodation 1 1 1 Live with parents 1 1 1 1 1 Number of other people in household 1 1 1 1 1 Father step father 1 1 1 1 1 Mother step mother 1 1 1 1 1 Brother step brother 1 1 1 1 1 Sister step sister 1 1 1 1 1 Husband wife de facto 1 1 1 1 1 Partner 1 1 1 1 1 Boyfriend girlfriend 1 1 1 1 1 Own children 1 1 1 1 1 Other relatives 1 1 1 1 1 Non relatives 1 1 1 1 1 Father in law partner s father 1 1 1 Mother in law partner s mot
66. n 25 The interpretation of the confidence intervals for all respondents table 10 is we are 95 confident that the true population estimate of Year 12 completion lies between 18 78 and 20 82 ae LSAY 2006 cohort user guide Classifications and code frames There are a number of variables contained in the LSAY datasets that are coded using standard classifications The information for these variables is collected using open ended guestions and verbatim responses are recorded These responses are then coded using standard classifications The details of these classifications are not provided in the data elements documents because they are very lensthy and can be summarised in a variety of ways This section provides a summary of the classifications and code frames used for each survey wave and references the relevant classifications and code frames Table 12 Summary of classifications and code frames used in the LSAY Y06 dataset Wave year Education Occupation Industry Institution 1 2006 ISCED 97 ISCO 88 Not applicable Not applicable ANZSCO 1st edition 2 2007 ASCED ANZSCO 1st edition ANZSIC 2006 Institution code frame 3 2008 ASCED ANZSCO 1st edition ANZSIC 2006 Institution code frame 4 2009 ASCED ANZSCO 1st edition ANZSIC 2006 Institution code frame 5 2010 ASCED ANZSCO 1st edition ANZSIC 2006 Institution code frame Notes ISCED International Standard Classification of Education ASCED Australian Standard Classification
67. n level XCELYYYY Highest school level completed XHSLYYYY Highest qualification level completed XHELYYYY Study status in VET XVETYYYY Study status in bachelor degree or higher XBACYYYY Full time or part time study status XFTSYYYY Completed Year 12 or certificate II or higher X122YYYY Completed Year 12 or certificate III or higher XI23YYYY Employment Labour force status XLFSYYYY Full time or part time employment status XFIPYYYY Permanent or casual employment XEMPYYYY Status in apprenticeship traineeship XATRYYYY Job mobility during last year XMOBYYYY Occupation 1 digit ANZSCO first edition XOCCYYYY Average weekly pay XWKPYYYY Average hourly pay XHRPYYYY Average weekly hours worked XHRSYYYY Any spell of unemployment during the year XUNEYYYY In full time employment or full time education XFTEYYYY Social Marital status XMARYYYY Living with parent s XATHYYYY Living in own home XOWNYYYY Number of dependent children XCHIYYYY NCVER CO Sample and survey design In 2006 a nationally representative sample of 15 year old students was selected to participate in PISA conducted by OECD 14 170 students were selected The initial LSAY survey wave wave 1 for 2006 was integrated with PISA and this group of young people became the fourth LSAY cohort The 2006 PISA sample comprised 356 schools from all states and territories This sample was designed to be representative of students across Australia using state territory school sector and region
68. n wave 4 technical documentation Corrected original population size from which sample was drawn from 234 490 to 234 940 Modified derived variable labels Updated Appendix A Updates to the Y06 dataset to reflect changes to the latest version of the dataset June 2010 1 0 Original version of user guide Contents Tables and figures Tables Figures Background Using this suide Registration The Y06 cohort Technical documents guestionnaires freguency tables and code books Cohort reports Other technical papers Accessing the data Specific data reguests LSAY data releases Data restrictions Overview of the guestionnaires Programme for International Student Assessment PISA Plausible values How do use plausible values The LSAY guestionnaires The LSAY data Topic areas Topic maps Data elements Variable listing metadata workbook Variable selection Variable naming conventions PISA variables LSAY standard variables LSAY non standard variables Derived variables Sample and survey design Response rates Sources of error Non sampling error Non response Weights Sampling error Standard errors NCVER 10 10 11 11 13 13 13 14 16 16 17 17 18 19 19 21 22 23 23 25 25 26 27 29 30 30 30 31 31 31 33 33 Confidence intervals 33 Relative standard errors 33 Examples 34 Classifications and code frames 35 Education 35 Occupation 36 Industry 3
69. nce subject Business Business subject Humanities SOSE Humanities SOSE subject Arts Arts subject Health PE Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Health PE subject 4 4 4 Computing 1 1 1 Computing subject 4 4 4 Home Economics 1 1 1 Home Economics subject 4 4 4 Technology 1 1 1 Technology subject 4 4 4 Other 1 1 1 Other subject 4 4 4 Subjects courses VET VET subjects 1 1 1 1 Number of VET subjects 1 1 1 Awarded VET certificate 1 1 VET subjects part of i i i apprenticeship traineeship VET subjects at school 1 1 1 VET subjects at TAFE 1 1 1 VET subjects at other training i 1 1 organisation TAFE subjects 1 TAFE subjects part of apprenticeship traineeship English subject is VET 4 4 4 LOTE subject is VET 4 4 4 Maths subject is VET 4 4 4 Science subject is VET 4 4 4 Business subject is VET 4 4 4 Humanities SOSE subject is VET 4 4 4 Arts subject is VET 4 4 4 Health PE subject is VET 4 4 4 Computing subject is VET 4 4 4 Home Economics subject is VET 4 4 4 Technology subject is VET 4 4 4 Other subject is VET 4 4 4 School plans Plan to complete Year 12 1 1 1 1 LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Careers advice Talked to careers guidance officer 1 1 1 Talked with person in desired job 1 1 1 Questionnaire 1 1 1 Read information 1 1 1 Visited workplace 1 1 1 University informat
70. oking for work 14 19 19 19 19 Registered with Centrelink 1 1 1 1 1 Checked Centrelink touch i i i i i screens computers Checked registered with Job i i i i i Network Job Services member Checked registered with any other i i i i employment agency Looked at advertisements in i 1 1 i 1 newspaper on the internet Answered advertisements in i 1 1 1 i newspapers on the internet Contacted friends or relatives 1 1 1 1 1 Written phoned approached an j i i i employer about a job Checked workplace noticeboards 1 1 1 1 1 Asked school or another organisation i i i i i for advice Posted resume on the internet checked i for replies Advertised tendered for work 1 1 1 1 Any other job search activity 1 1 1 1 1 Problems looking for work Health problems or some disability 1 1 1 1 1 Employers think you are too young 1 1 1 Problems with childcare 1 1 1 1 1 Don t have suitable transport 1 1 1 1 1 NCVER Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Not enough of the right kind of education l i Don t have enough work experience 1 1 1 1 1 Not enough jobs available 1 1 1 1 1 Gender 1 1 1 1 1 Racial ethnic background 1 1 1 1 1 Need better reading and writing skills 1 1 1 1 1 Don t have good interview skills 1 1 1 1 1 Lack of skills in writing job applications 1 1 1 1 1 Lack confidence 1 1 1 1 1 Not good with numbers 1 1 1 1 1 Poor language or communication skills 1 1 Age gender or other discriminatio
71. ology questionnaire IC Most PISA variables are named using the following convention guestionnaire component guestion number and guestion part where applicable For example the variable ST16001 is question number 16 from the student questionnaire ST34003 is question number 34 part c from the student questionnaire 1C01001 is question number 1 from the information communication technology questionnaire Figure 8 PISA variable naming convention PISA student questionnaire ST34003 Ouestion 34 Part 3 c Countries are also able to introduce country specific questions in the PISA questionnaires referred to as national options questions These are denoted by the character N for example ST44N01 rather than the character Q Plausible values are used to report student achievement in PISA There are five plausible values for each of the domains and sub domains and the PISA student achievement variables take this information into account in the variable name For example the variable PV1MATH points to the first plausible value in the maths domain PV4SCIE points to the fourth plausible value in the science domain PV1INTR points to the first plausible value in the first sub domain Interest in science PV3SUPP points to the third plausible value in the second sub domain Support for scientific inguiry Replicate weights have been used to estimate sampling variances fo
72. on level XFTS2009 362 Completed Year 12 or X1222009 Changes to Completed Year 12 or certificate II or higher due to correction made to 10 certificate II or higher Highest qualification level Completed Year 12 or X12232009 Changes to Completed Year 12 or certificate II or higher due to correction made to 8 certificate III or higher Highest qualification level Average hourly pay XHRP2009 Correction due to typographical error in calculation 37 In full time employment XFTE2008 Changes to In full time employment or full time education due to correction made to 11 or full time education Current qualification level XFTE2009 9 Minor modifications made to some derived variables Added not applicable category for those who are not employed or not in the labour force Average weekly pay XWKP2006 8727 XWKP2007 3759 XWKP2008 2839 Average hourly pay XHRP2006 8727 XHRP2007 3759 XHRP2008 2839 Average weekly hours XHRS2006 8727 worked XHRS2007 3759 XHRS2008 2839 XHRS2009 8727 Waves 1 to 4 Version 28 March 2011 Minor changes made to derived variable labels and formats 2006 to 2009 3 1 Wave year Version Date published Variable Variable Description Number of name observations affected Current school level XCSL Highest school level XHSL completed Current qualification XCEL level Highest qualification XHEL level completed Full time or part time XFTS study status Study status in bachelor XBAC degree or h
73. onditions Responsibility Change of work conditions Promotion Part time casual Labour force status derived variable Permanent or casual employment derived variable Occupation 1 digit ANZSCO First Edition derived variable Job mobility during last year derived variable Any spell of unemployment during the year derived variable Time worked NCVER Hours worked per week present job Hours worked per week main job if more than one Hours worked per week all jobs if more than one Hours worked per week job reported at last interview Hours worked per week weekdays Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Hours worked per week weekend 1 Months worked 14 Months worked full time 19 19 19 19 Months worked part time 19 19 19 19 No full time work since last interview 1 1 1 1 No part time work since last interview 1 1 1 1 Full time or part time employment i i 1 1 i i status derived variable Average weekly hours worked derived i 1 1 i i variable Wages and benefits Freguency of pay 1 1 1 1 1 1 Gross pay 1 1 1 1 1 Annual salary 1 1 1 1 1 Hourly rate 1 1 1 1 1 Average weekly earnings 1 1 1 1 1 Take home pay dollars 1 Take home pay cents 1 Take home pay 1 1 1 1 1 Pay type 1 Annual sick leave 1 1 1 1 1 Average weekly pay derived variable 1 1 1 1 1 1 Average hourly pay derived variable 1 1 1 1 1 1 Starting work Month b
74. or cadetship Sources of income Scholarship Sources of income Cadetship Sources of income Other government allowance Sources of income Other 1 Sources of income None 1 Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Course fees None 1 1 1 1 1 Course fees Respondent 1 1 1 1 1 Course fees Parents family 1 1 1 1 1 Course fees Employer 1 1 1 1 1 Course fees Government 1 1 1 1 1 Course fees Other 1 1 1 1 1 Commonwealth supported HECS 1 1 1 1 1 Commonwealth supported HECS full i j j i i fee paying Full fee paying 1 1 1 1 Full fee paying FEE HELP 1 Full fee paying up front 1 Full fee paying payment scheme 1 Full fee paying employer 1 Full fee paying scholarship 1 Economic climate Study undertaken 1 1 Subjects courses 1 1 Study plans 1 1 Work experience Influence post school plans 1 1 Influence future plans 1 1 LSAY 2006 cohort user guide Topic map 6 Employment Current Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Employment characteristics Work in job business farm Still have job reported at last interview Away from job School holiday job More than one job Number of other jobs had Wages salary self employed Kind of work ANZSCO Employer s main kind of business ANZSIC Change of work conditions Pay Change of work conditions Skills Change of work c
75. other reproduction and rights should be directed to the National Centre for Vocational Education Research NCVER This document should be attributed as NCVER 2013 Longitudinal Surveys of Australian Youth LSAY 2006 cohort user guide NCVER Adelaide This work has been produced by NCVER through the Longitudinal Surveys of Australian Youth LSAY Program on behalf of the Australian Government and state and territory governments with funding provided through the Australian Department of Education Employment and Workplace Relations TD TNC 106 15 Published by NCVER ABN 87 007 967 311 Level 11 33 King William Street Adelaide SA 5000 PO Box 8288 Station Arcade Adelaide SA 5000 Australia P 61 8 8230 8400 F 61 8 8212 3436 E lsay ncver edu au W lt http www lsay edu au gt User guide updates Date Version Update March 2013 3 0 Updated for latest data release wave 6 2011 January 2012 2 0 Updated for latest data release wave 5 2010 Added reference to newly released weighting technical paper Added additional reference to PISA 2006 technical reports Updated information relating to data archive data now available from the Australian Data Archive ADA rather than the Australian Social Science Data Archive ASSDA Added information about population weights to table about variable naming conventions March 2011 11 Added information on LSAY website registration Added information o
76. pears within a wave This is equivalent to the number of variables that correspond to the data element in a single wave Topic map 1 Demographics Student contains demographic information relating to respondents place of residence gender Indigenous status date of birth and age country of birth language spoken at home and socioeconomic status Topic map 2 Demographics Parent contains demographic information relating to the country of birth occupation and education levels of a respondent s mother and father Topic map 3 Education School contains school education information relating to respondents school characteristics student characteristics reasons for attending their school extracurricular activities student achievement perceptions about self and school views on science use of computers time spent learning study plans careers advice work experience workplace learning subjects and courses undertaken qualifications and results and receipt of government payments Topic map 4 Education School transition contains school transition information about intentions and reasons for leaving school post school plans and school leavers main activity since leaving school Topic map 5 Education Post school contains post school education information relating to study including current and past study apprenticeships and traineeships qualifications obtained reasons for withd
77. r population estimates derived from a complex sample design The weights are simply named chronologically from W FSTR1 to W FSTR80 The variable W FSTUWT is the final student weight 2 The Australian PISA 2006 major assessment domains are reading mathematics and science The PISA 2006 science sub domains are interest in science support for scientific inguiry explaining phenomena scientifically identifying scientific issues and using scientific evidence NCVER CO Detailed information about plausible values and replicate weights is available from the OECD PISA 2006 data analysis manuals located at lt http www oecd org document 38 0 3343 en 32252351 32236191 42609254 1 1 1 1 00 html gt Two types of indices are provided in the PISA dataset simple indices and scale indices Simple indices are constructed by arithmetically transforming or recoding one or more items for example age Scale indices combine several answers provided by students or principals to build a broader not directly observable concept For example CULTPOSS is a student level scale index derived from cultural possessions such as classic literature and books of poetry Simple and scale indices appear towards the end of the PISA data and tend to be descriptive rather than carrying a variable naming convention Table5 Summary of PISA variable naming conventions PISA variable Examples of PISA Description variable names Standard variables ST16Q01 The first t
78. rawing deferring from study changes in study status and or details including changes to course institution employer and apprentice or traineeship satisfaction with study careers advice perceptions about post school study and government payments and income It is worth noting that within the following minor topic areas Study may refer to past and or current study as well as apprenticeships and traineeships for some waves Current study may refer to apprenticeships and traineeships for some waves Past study may refer to apprenticeships and traineeships for some waves Apprenticeship traineeships may refer to past and or current apprenticeships for some waves Topic map 6 Employment Current contains the respondents current employment including employment characteristics time worked wages and benefits when started and left work reasons for leaving work employment while at school post school employment job training and job satisfaction Topic map 7 Employment Job history and training contains respondents job history and training information including any other employment currently undertaken by the respondent relating to employment characteristics time worked wages and benefits job training undertaken reasons for leaving work and perceptions about work nev Topic map 8 Employment Seeking employment contains information about respondents
79. s Teaches what work is really like Teaches about people Teaches about instructions Teaches about thinking for self Teaches about confidence Teaches about job skills Teaches about work conditions Teaches about your future career Qualifications and results NCVER Awarded certificate Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Received any other certificate 1 1 1 1 Certificate name 1 1 1 1 Received state specific score 1 1 1 1 Result known 1 1 1 1 Result given 1 1 1 1 Result 1 1 1 1 Highest school level completed f 1 1 1 1 1 1 derived variable Completed Year 12 or certificate II or i 1 1 i i higher derived variable Completed Year 12 or certificate III or i i i i i higher derived variable Government payments f Receive Youth Allowance ABSTUDY 1 1 1 and income Fortnightly Youth Allowance ABSTUDY i i i payment Stay on at school without Youth i i i Allowance ABSTUDY Economic climate Stay on at school 1 Study plans 1 Subjects courses 1 LSAY 2006 cohort user guide Topic map 4 Education School transition Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Post school plans Student plans Student plans immediate Student plans eventual Parents plans Friends plans Study plans Study plans type Study plans timeframe nfluence Family nfluence Friends nfluence
80. study and i 1 1 i 1 study work commitments Reason Wanted i EO f 1 1 1 1 1 job apprenticeship traineeship Reason Financially difficult 1 1 1 1 1 Reason Lost interest 1 1 1 1 1 Reason Never wanted to study 1 1 1 1 1 Reason Course was not what you 4 i i i i wanted Reason Wouldn t have led to good 1 i 1 i i job career Reason Poor results 1 1 1 1 1 Reason Study load 1 1 1 1 1 Reason Never intended to complete i 1 1 1 i the course Reason Access transport 1 1 1 1 1 Reason Health personal reasons 1 1 1 1 1 Reason Main reason 1 1 1 1 1 Changed institutions Same institution 5 7 7 7 7 Reason Not first choice 5 7 7 7 7 Reason Better guality education 5 7 7 7 7 Reason Poor results 5 7 7 7 7 Reason Course was not what you 5 7 7 7 7 wanted Reason Course not available at first 5 7 7 7 7 institution LSAY 2006 cohort user guide Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Reason Access transport 5 7 7 7 7 Reason Health personal reasons 5 7 7 7 7 Reason Main reason 5 7 7 7 7 Changed course Same course 2 2 2 2 Reason Course costs 1 2 2 2 2 Reason Pre requisite 1 2 2 2 2 Reason Didn t like course 1 2 2 2 2 Reason Course was not what you wanted Reason Better career prospects 1 2 2 2 2 Reason Poor results 1 2 2 2 2 Reason Study load 1 2 2 2 2 Reason Preferred to do second course 1 2 2 2 2 Reason Health personal reasons 1 2 2 2 2 Reason
81. ta file deposited with the Australian Data Archive Users are encouraged to download the most recent version of the data to ensure all updates are included Note that the version numbering convention adopted by the Australian Data Archive and reflected in the table below has been in place from the time the 2008 datasets were deposited Table 13 Summary of changes made to the Y06 data file Wave year Version Date published Variable Variable Description Number of name observations affected Waves 1 to 6 Version March 2013 Wave 6 2011 variables added to data file 2006 to 2011 5 School postcode from wave 1 variable added to data file Corrections and modifications to some derived variables Current qualification XCEL2007 Respondents who were undertaking an apprentice traineeship and whose qualification level to type was a short course or recreational course single module subject only unknown or XCEL2008 some other qualification than those listed were previously derived as not studying for a qualification The derivation has been modified so that these respondents are now derived as undertaking a certificate at an unknown qualification level XCEL2007 3 XCEL2008 5 XCEL2009 Changes to Current qualification level due to correction made to Current qualification 55 level in previous year Respondents who were undertaking an apprentice traineeship and whose qualification type was a short course or recreational course single modul
82. tandard errors will have wide confidence intervals The mathematical derivation of a 95 confidence interval for a proportion is px2xselp where is the estimate obtained from the sample and se p is the standard error of the estimate typically obtained from a statistical analysis package Relative standard errors The relative standard error RSE is a standardised measure that enables the comparison between different estimates in terms of their reliability The RSE is derived by dividing the standard error of the estimate by the estimate itself expressed as a percentage RSE p LP x100 p 3 For further information on this technique users should consult William Cochran Sampling techniques 3rd edn John Wiley and Sons New York 1977 sections 11 18 11 19 11 20 NCVER a Examples Consider the following estimates of highest school level completed XHSL2008 to 2008 taken from the Y06 cohort reports In this example estimates obtained from a large sample are compared with estimates obtained from a small sample Table 10 presents the highest school level for all respondents larse sample while table 11 presents the highest school level obtained for those from remote areas small sample Table 10 Estimates standard errors RSEs and confidence limits for highest school level completed Y06 cohort in 2008 for a large sample all respondents Year level Freguency Standard RSE 95 confidence interval error of
83. the two characters WT either ACHOSWT at the beginning or end of the variable name WT2009 Two sets of weight variables are produced the first reproduces WTO9GEN_P the sample sizes in each wave and the second denoted by _P reproduces the population size at each wave ACH09WT P f OR m For further information about weights see section Weights in WT2009 P the chapter Sample and survey design ae LSAY 2006 cohort user guide Derived variables A series of derived variables has been developed to simplify use of the LSAY data and provide useful measures indicators for analysis The derived variables focus on the areas of educational attainment employment measures of engagement in study and work and social indicators Table 7 summarises the series of derived variables available on the Y06 dataset Derived variables are denoted by the character X followed by three characters uniguely identifying the derived variable followed by four digits for the survey year Detailed technical documentation outlining how the variables are derived as well as their properties is forthcoming and will be linked to this document when it becomes available In the meantime data users can reguest further information about the derived variables from NCVER via email lt lsay ncver edu au gt Table 7 Derived variables Indicators Derived variable Variable name Education Current school level XCSLYYYY Current qualificatio
84. tion ae LSAY 2006 cohort user guide Table4 User guide data element documents User guide Major topic area Sub major topic area s Part A Demographics Student Parent Part B1 Education School School transition Part B2 Education Post school Part C Employment Current Job history and training Seeking employment Not in the labour force Part D Social Health living arrangements and finance General attitudes Variable listing metadata workbook To further assist in the use of the LSAY data an Excel metadata workbook has been developed It provides a complete listing of all the variables in the Y06 dataset as well as information about each variable The information contained in this workbook is similar to that contained in the topic maps and data elements documents but can be manipulated using filters to search for and to group variables Data can be filtered and inspected by wave year questionnaire section topic area s and or data element The metadata workbook can be accessed at lt www lsay edu au publications 2258 html gt under the supporting documents tab There are two worksheets included in the metadata workbook Variables and Values Both worksheets list each variable in the order it appears in the dataset Major sub major and minor topic areas as well as data elements are provided for each variable The wave year questionnaire section and variable label are also included where applicable Th
85. to Study status in VET due to corrections made to Current qualification level 20 Changes to Study status in VET due to corrections made to Study status in VET in previous year Some respondents who had indicated in a previous interview that they had commenced VET study training but did not confirm that course of study training in the current interview were derived as having commenced but not completed study in VET This derivation has been modified and these respondents are now derived as having never commenced VET study Changes to Study status in VET due to corrections made to Current qualification level 39 Changes to Study status in VET due to corrections made to Study status in VET in previous year One respondent who had indicated in a previous interview that they had commenced VET study training but did not confirm that course of study training in the current interview was derived as having commenced but not completed study in VET This derivation has been modified and this respondent is now derived as having never commenced VET study Wave year Version Date published Variable Variable Description Number of name observations affected Some respondents who had commenced VET study training in a previous interview but had missed their last interview were incorrectly derived as having never commenced VET study This derivation has been corrected and these respondents are now derived as having completed VET stud
86. to participate in the Programme for International Student Assessment PISA conducted by the Organisation for Economic Co operation and Development OECD This sample became the fourth cohort of the LSAY program This is referred to as the LSAY Y06 cohort The PISA sample was constructed by randomly selecting 50 students aged 15 years from a sample of schools designed to represent all states and sectors In Australia 356 schools and 14 170 students participated in PISA Assessments in mathematical literacy reading literacy and scientific literacy were administered in their schools to provide information on student achievement Students also completed a background questionnaire about their families their views on a range of science related issues the environment educational and vocational plans attitudes to school and learning work experience workplace learning and part time work In 2007 members of the Y06 cohort were contacted for their annual LSAY telephone interview conducted by the Wallis Consulting Group and have been contacted annually ever since The questionnaire for their 2007 interview included questions on school transitions from school post school education and training work job history job search history non labour force activities health living arrangements and finance and general attitudes Subsequent surveys asked similar questions but with the emphasis changing from school to post school education training and wor
87. trata 2 Attrition weights are used to address unit non response by ensuring that the distribution of the sample matches the distribution of the sample population Attrition weights used in LSAY account for wave on wave attrition from the first wave In calculating attrition weights a non response analysis was undertaken to determine the factors that contributed to attrition The use of attrition weights ensures that distributions in each wave match those obtained in PISA for the factors identified as contributing to attrition Logistic regressions have been used to calculate attrition weights The response variable of whether or not a respondent replied to the survey in a given year was regressed against a series of factors that may contribute to non response The inverse of the predicted probability of responding then forms the attrition weights The final LSAY weights for each wave combine both the sample and attrition weights Two sets of final weights are produced The first reproduces the sample sizes in each wave and the second reproduces the population size 234 940 at each wave In both cases the distributions in each wave match those obtained in the original population Users must be aware that bias resulting from survey attrition may not be fully accounted for in the weighting strategies used To allow users to determine the effectiveness of the attrition weights data in the cohort report demographic tables are presented both weight
88. udent life meets 1 1 1 1 1 expectations mpressions Made close friends 1 1 1 1 1 Problems Paying fees 1 1 1 1 1 Problems Juggling study and work i 1 1 i i commitments Problems Course more difficult than i j i i expected Problems Conflict between family and 1 1 1 1 1 study Problems Caring for children or other i 1 1 1 i family members Problems Balancing personal i 1 1 i i relationships Problems Fitting in with other students i 1 1 i i and making friends Problems Finding time for other 1 1 1 1 1 commitments LSAY 2006 cohort user guide Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Problems Other 1 Problems None 1 Problems Main problem 1 1 1 1 1 1 1 Careers advice Careers guidance officer Questionnaire Job application assistance Information about further study Online tool Source Educational institution Source Government agency Source Employer program Source Private provider you paid Source Internet Source Family friends Source Current employer Source Other Source Unknown Usefulness Reason for not accessing careers advice Government payments and income NCVER Sources of income Youth Allowance ABSTUDY Amount of Youth Allowance ABSTUDY 1 Youth Allowance ABSTUDY independent dependent Sources of income Paid work 1 Sources of income Parents or family 1 Sources of income Scholarship
89. ught to prepare for job interview by recruitment employment agencies Taught to find age suitable Taught to find age suitable school Taught to find age suitable family Taught to find age suitable myself Taught to find age suitable career expos advisors Taught to find age suitable other source Taught to find age suitable social community workers Taught to find age suitable Job Guide Taught to find age suitable media Taught to find age suitable through education Taught to find age suitable friend acquaintances jobs jobs at jobs by jobs by jobs by jobs by jobs by jobs by the jobs by the jobs jobs by Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Taught to find age suitable jobs by recruitment employment agencies Taught to find information about post study jobs Taught to find information about post study jobs at school Taught to find information about post study jobs by family Taught to find information about post study jobs by myself Taught to find information about post study jobs by career expos advisors Taught to find information about post study jobs by other source Taught to find information about post study jobs by social community 1 workers Taught to find information about post study jobs by the Job Guide Taught to find information about post study jobs
90. vention mentioned above These variables are summarised in the following table Table6 Summary of LSAY non standard variable naming conventions Non standard Examples of non Description variable standard variable names Demographics INDIG Some demographic variables such as Indigenous status tend to be descriptive rather than carrying a naming convention School characteristics STATE School characteristics such as state of the school and school SECTOR sector tend to be descriptive rather than carrying a naming convention Derived variables XLFS2007 Derived variables have been constructed across all waves to XCEL2008 summarise key information such as labour force status and current education level For further information about derived variables see the section Derived variables IN flag IN2006 IN flags have been created for each survey year to indicate IN2008 whether a respondent participated in the survey in that year If the value of the IN flag is equal to 1 this indicates that the respondent participated in the survey for that year IN flag variables are denoted by the two characters IN followed by four digits for the survey year Interview dates LBWID Day of interview month of interview and year of interview are LBWIM collected each survey year and consolidated into an interview LBWIY date variable INTDATO9 Interview date variables use the same variable naming convention for the first two char
91. wo characters indicate the questionnaire instrument IC05Q01 The PISA questionnaire instruments are the student ST34Q03 questionnaire ST and the information communication technology questionnaire IC The following two digits indicate the question number e g ST16 is question 16 from the student questionnaire The final three characters are the question part or sub section So ST34Q03 is part 3 of question 34 from the student questionnaire National options ST46N01 The fifth character N rather than Q indicates that the question is a national options question i e a national not international question Student achievement PV1SCIE The first two characters PV indicate the variable is a plausible plausible values PV1INTR value The next character indicates whether it is the first PV4SUPP plausible value up to the fifth plausible value The next four characters indicate the domain or sub domain PV1SCIE indicates that the variable is a science domain while PV1INTR indicates that the variable is from the interest in science science sub domain For further information on plausible values see section Overview of the questionnaires Plausible values PISA weights W FSTR1 Replicate weights are identified using the characters W_FSTR W_FSTR80 followed by a chronological number W_FSTUWT W_FSTUWT is the final student weight CNTFAC E CNTFAC are country weight factors for equal weights CNTFAC
92. y of clearing debt on credit card s Shortage of money Sold something because you needed money Shortage of money Went without meals Shortage of money Had to ask family or friends for money Shortage of money Had to borrow money Shortage of money Didn t get medicines or go to a doctor Shortage of money Couldn t buy text books or other study materials Shortage of money Couldn t buy other things you needed Shortage of money Couldn t pay electricity gas or telephone bills Shortage of money Couldn t pay mortgage rent on time Shortage of money Couldn t afford to heat your home Able to save money Frequency of saving money Managing financially NCVER Topic map 11 Social General attitudes Minor topic area Data element 1 2006 2 2007 Wave Year 3 2008 4 2009 5 2010 6 2011 Leisure Hours spent watching TV 1 Hours spent listening to music 1 Hours spent playing sport 1 Hours spent reading for pleasure 1 Hours spent doing unpaid volunteer i work Go to the library 1 1 1 1 Read books 1 1 1 1 Read newspapers or magazines 1 1 1 1 Use the internet 1 1 1 1 Play computer video games 1 1 1 1 Play sport or do exercise 1 1 1 1 Community activities 1 1 1 1 Go to church place of worship 1 1 1 1 Volunteer 1 1 1 Interests Learning new things 1 Thinking about why the world is in its 1 current state Finding out why things happened 1 Finding out more about things you do 1 not
93. y or commenced but did not complete VET study One respondent whose highest education level was a bachelor degree or higher level qualification and had also completed VET study training was incorrectly derived as having never commenced VET study This derivation has been corrected and this respondent is now derived as having completed VET study Status in XATR2010 A variable was previously missing from the derivation and some respondents who were 705 apprenticeship traineesh undertaking had completed or had commenced and not completed an ip apprentice traineeship were incorrectly derived as having never commenced an apprentice traineeship This derivation has been corrected and these respondents are now derived as either undertaking completed or commenced and not completed an apprentice traineeship Job mobility during last XMOB2010 Incorrect variables were used in the derivation variables from the previous survey wave 2357 year were used rather than the current survey wave This has been corrected and respondents job mobility is now correctly derived Average hourly pay XHRP2010 Respondents who provided their annual pay and whose hours worked were known were 70 incorrectly derived as having an unknown hourly pay This derivation has been corrected and the hourly pay for these respondents is now correctly derived In full time employment XFTE2007 Change to In full time employment or full time education due to correction made to Full or full ti
94. y type Other second job Pay type Other third job Gross weekly pay Other second job Gross weekly pay Other third job Average weekly earnings Other second job Average weekly earnings Other third job Hourly rate Other second job Hourly rate Other third job Annual salary Other second job Annual salary Other third job NCVER Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Job training Classroom based training 1 1 1 1 1 Hours of classroom based training 1 1 1 1 1 Training outside workplace 1 1 1 1 1 Hours of training outside workplace 1 1 1 1 1 On the job training 1 1 1 1 1 Training helped get promotion or pay i j 4 i i rise Training could help to get more i j i i i responsibility Training could help to get different type i i 1 i i of job Suitable amount of training received 1 1 1 1 1 Leaving work Main reason left job 1 3 3 3 3 Month left job 2 2 2 2 Year left job 2 2 2 2 Way in which next job was better 1 1 1 1 LSAY 2006 cohort user guide Topic map 8 Employment Seeking employment Wave Year Minor topic area Data element 1 2006 2 2007 3 2008 4 2009 5 2010 6 2011 Looking for work Looking for work in the last 4 weeks 1 1 1 1 1 Looking for full time or part time work 1 1 1 1 1 Prefer full time work 1 1 1 1 1 Available for work last week 1 1 1 1 1 Job search activity Looked for work 1 1 1 1 1 Number of weeks looking for work 1 1 1 1 Months lo

LSAY user guide Y06 March 2013 update

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