SN 5760 - 5760 - Growing Up in Scotland - Sweep 2
Contents
1. 24User Guide 24 Appendix A Full non response models Table A1 Full model for non response to sweep 2 interview birth cohort Variables in the Equation S E Wald Sig Household income 13 7 4 0 01 Less than 9 999 baseline 10 000 19 999 0 14 0 13 1 1 1 0 30 1 15 20 000 31 999 0 15 0 16 0 9 1 0 35 1 16 32 000 or more 0 25 0 18 2 0 1 0 16 1 28 Missing 0 29 0 16 3 3 1 0 07 0 75 Tenure 21 1 2 0 00 Owner occupier 0 59 0 14 18 8 1 0 00 1 80 Rents HA council 0 52 0 14 14 5 1 0 00 1 68 Rents private baseline Family type 11 2 1 0 00 Lone parent family 0 40 0 12 11 2 1 0 00 0 67 Couple family baseline Ethnicity of respondent 16 4 1 0 00 White ethnic background 0 74 0 18 16 4 1 0 00 2 09 Other ethnic background baseline Selected child was breastfed 10 0 1 0 00 Yes 0 29 0 09 10 0 1 0 00 1 34 No baseline Scottish Index of Multiple Deprivation 11 4 4 0 02 Least deprived 0 5393 7 7347 0 21 0 16 1 7 1 0 19 1 23 7 7354 13 5231 0 24 0 14 3 0 1 0 09 1 28 13 5303 21 0301 0 43 0 14 9 9 1 0 00 1 53 21 0421 33 5214 0 05 0 12 0 2 1 0 69 1 05 33 5277 87 5665 most deprived baseline Respondent regularly attended baby groups in the past year 5 6 1 0 02 Yes 0 23 0 10 5 6 1 0 02 1 26 No baseline Constant 0 07 0 65 0 0 1 0 91 0 93 Notes Outcome is 1 respondent gave a sweep 2 interview 0 no sweep 2 interview Base is all households eligible for sweep 2 in the birth cohort n 5 185 R2. Variables names are made up of 8 characters the first indicates the source of the variable the second the year of collection and the rest is an indication of the question topic Therefore where the same question was asked in Sweep 1 and Sweep 2 the names will be the same apart from the second character If a variable name has changed substantially between sweeps this is marked in the variable list The naming convention is summarised in the table overleaf 6 3 Variable labels In the Sweep 2 dataset the variable labels are restricted to 40 characters the first 2 show the source and year of the data as in the variable name Although the labels give an indication of the topic of the question it is essential to refer to the questionnaire to see the full text of the question The variable list shows the page numbers of the relevant questionnaire section 6 4 Derived variables Derived variables included in the dataset are listed with the questionnaire variables for the same topic The SPSS syntax used to create them can be found in the Derived Variables section of the documentation 11User Guide 11 GUS Variable Naming Convention Character Source Type of lettering no DWP variable CG Partner s interview Scale variable 1 3 4 5 amp 6 788 Source of data Sweep Wave Key theme prefix Sub theme stem Question Varia Non sequential Capitals Sequential lower case a b c Non sequential Abbreviated lower 01
3. The National Statistics Socio economic Classification NS SEC is a social classification system that attempts to classify groups on the basis of employment relations based on characteristics such as career prospects autonomy mode of payment and period of notice There are fourteen operational categories representing different groups of occupations for example higher and lower managerial higher and lower professional and a further three residual categories for full time students occupations that cannot be classified due to a lack of information or other reasons The operational categories may be collapsed to form a nine eight five or three category system The Growing Up in Scotland dataset includes the five category system in which respondents and their partner where applicable are classified as managerial and professional intermediate small employers and own account workers lower supervisory and technical and semi routine and routine occupations Further information on NS SEC is available from the National Statistics website at http www statistics gov uk methods quality ns_sec cat_subcat_class asp 6 7 2 Area level variables Scottish Government Urban Rural Classification The Scottish Government Urban Rural Classification was first released in 2000 and is consistent with the Government s core definition of rurality which defines settlements of 3 000 or less people to be rural It also classifies areas as remote based on drive
4. The models are given in full in the Appendix 8User Guide 8 Partners in both cohorts were less likely to respond if the mother was not working unless the partner was also not working However couples in households where neither partner worked more than 16 hours per week were more likely to respond Table 5 4 Characteristics associated with partner response behaviour in the birth cohort Characteristics associated with response Characteristics associated with non response Mother older 40 Younger mother lt 30 Educated to Higher or above No qualifications First time mother Other children in household Child white ethnic background Child other ethnic background Mother works full time Mother does not work Neither parent in work Both parents work 16 hours a week Table 5 5 Characteristics associated with partner response behaviour in the child cohort Characteristics associated with response Characteristics associated with non response Household is in remote or very remote town Household is in large urban area or household is in accessible small town First time mother Other children in household Child white ethnic background Child other ethnic background Mother works full time Mother does not work Neither parent in work Both parents work 16 hours a week 5 3 2 Final partner weights The final partner weight is the product of the partner non response weight and the sweep 2
5. 99 Pe Sweep code Area Level Derived i See Theme prefix See Stem dictionary dictionary Cohort 1 Sweep 1 2005 06 Derived Cohort 1 Sweep variable from 2 2006 07 partner int Cohort 1 Sweep O a Main carer adult interview Weights and Heights 12User Guide 6 5 Household data In addition to the questions asked about the child and parents the respondent was also asked about each household member The gender age and marital status of each household member was collected Each person was identified by their person number which they will retain though each sweep of the survey The variable MbHGSI n can be used to see whether a person who was in the household at sweep 1 is in the household at sweep 2 A set of derived summary household variables is also included in the data Amongst other things these detail the number of adults number of children or number of natural parents in the household A list of these variables is included in Table 6 1 A set of variables which allow identification of the respondent and their partner if present in the household grid are also included These permit easier analysis of respondent and partner age marital status and relationship to other people in the household Table 6 1 Key household derived variables DbHGnmad Db Number of adults in household DbHGnmkd Db Number of children in household DbHGnmsb Db Number of siblings in household DbHGnp01 Db Number
6. Pilot in January 2006 2 Data collection methods 2 1 Mode of data collection Interviews were carried out in participants homes by trained social survey interviewers using laptop computers otherwise known as CAPI Computer Assisted Personal Interviewing The interview was quantitative and consisted almost entirely of closed questions There was a brief self complete section in the interview in which the respondent using the laptop input their responses directly into the questionnaire programme At sweep 1 primarily because of the inclusion of questions on the mother s pregnancy and birth of the sample child interviewers were instructed as far as possible to undertake the interview with the child s mother Where the child s mother was not available interviews were undertaken with the child s main carer At sweep 2 interviewers were instructed to undertake the interview with the sweep 1 respondent Where this was not possible or appropriate interviews were conducted with the child s main carer In practice most interviews were undertaken with the sweep 1 respondent and this was usually the child s mother 3User Guide 3 2 2 Length of Interview Overall the average interview lasted around 79 minutes The child cohort interview had a slightly longer average length at 82 minutes than the birth cohort interview at 78 minutes The median interview length for both cohorts was 70 minutes 2 3 Timing of fieldwork F
7. The final weights were scaled to the responding sweep 2 sample size to give a mean weight of one This makes the weighted sample size match the unweighted sample size Details of the weight variables are contained in section 6 9 Information on when to apply the weights is contained in section 5 5 5 3 Partner weights 5 3 1 Weighting method Partner interviews were carried out at sweep 2 of the survey Partner interviews were attempted in any household with live in partners Partners were not interviewed at sweeps 1 3 or 4 Whilst the response rate of the partners was good 79 in the birth cohort and 77 in the child cohort there could still be some bias if the partners who responded were systematically different from those that did not A bivariate analysis suggested the partner sample was biased and a set of weights was generated to reduce the effects of this The methods used are the same as those used to generate the main sweep 2 non response weights The difference was that information from the respondents sweep 2 interview could be used to model the response behaviour of the partners Again the data for the birth and child cohorts were modelled separately However the patterns in response behaviour were very similar and a number of variables appeared in both models The characteristics related to response behaviour identified by modelling partner response are given in Table 5 4 for the birth cohort and Table 5 5 for the child cohort
8. interview weight The weights were scaled to the responding sample size to give a mean weight of one This makes the weighted sample size match the unweighted sample size Details of the weight variables are contained in section 6 9 Information on when to apply the weights is contained in section 5 5 5 4 Sample efficiency Adding weights to a sample can affect the sample efficiency If the weights are very variable i e they have both very high and very low values the weighted estimates will have a larger variance More variance means standard errors are larger and confidence intervals are wider so there is less certainty over how close the estimates are to the true population value The effect of the sample design on the precision of survey estimates is indicated by the effective sample size neff The effective sample size measures the size of an unweighted simple random sample that would have provided the same precision standard error as the design being implemented If the effective sample size is close to the actual sample size then we have an efficient design with a good level of precision The lower the effective sample size the lower the level of precision The efficiency of a sample is given by the ratio of the effective sample size to the actual sample size The range of the weights the effective sample size and sample efficiency for both sets of weights are given in Table 5 6 9User Guide 9 Table 5 6 Effective sample siz
9. of natural parents in household DbHGrsp01 Db Whether respondent is natural mother DbHGrsp02 Db Whether respondent is natural father DbHGnp02_ Db Natural mother in household DbHGnp03_ Db Natural father in household DbHGrsp04 Db Respondent living with spouse partner DbMothID Db Person number of mother DbFathID Db Person number of father DbRespID Db Person number of respondent DbPartID Db Person number of partner DbRPAge Db Respondent partners age DbRPsex Db Respondent partners sex 6 6 Childcare data The childcare section of the CAPI questionnaire utilises feed forward data This technique allows information collected at the previous sweep to be fed forward into the current sweep s CAPI questionnaire for the respondent to confirm or change rather than such information being completely re collected This reduces respondent burden and allows for the saved time to be used elsewhere in the interview At sweep 2 for those cases where childcare had been used at sweep 1 details of sweep 1 arrangements including the provider name provider type the number of hours they looked after the child per week and the number of days over which those hours were spread were fed forward The respondent could confirm all details were still correct change the number of hours or days or indicate that the arrangement was no longer being used All respondents could also provide details of new arrangement
10. regularly uses childcare DaHacc01 Whether child had had an accident or injury for which they were taken to a doctor health centre or hospital MaHgen0o1 Selected child s general health MaObtg01 Respondent regularly attended any baby toddler groups in the past year MaBFDe01 Selected child was breastfed MaHdev01 Respondent has concerns about selected child s development learning or behaviour MaHpgn01 Respondent s general health MaHcig02 Respondent currently smokes cigarettes The model generated a predicted probability for each respondent This is the probability the respondent would take part in the sweep 2 interview given their characteristics and those of the household collected at sweep 1 Respondents with characteristics associated with non response such as being a private tenant are under represented in the final sweep 2 sample and will thus receive a low predicted probability The non response weights are then generated as the inverse of the predicted probabilities hence respondents who had a low predicted probability get a larger weight increasing their representation in the sample The birth and child cohorts were modelled separately although there were similarities between the two models The characteristics related to response behaviour at sweep 2 are given in Table 5 2 for the birth cohort and Table 5 3 for the child cohort The full models are given in the Appendix analysis Ineligible outcome codes include
11. vacant demolished derelict and non residential addresses 7User Guide 7 Table 5 2 Characteristics associated with response behaviour in the birth cohort Characteristics associated with response Characteristics associated with non response High income gt 32 000 Lower income or withheld information on income Owner occupiers Rent from a private landlord Live as a couple Lone parent family From a white ethnic background From any other ethnic background Breastfed the baby Did not breast feed Area deprivation score falls in the middle quintile Area deprivation score is in the lowest quintile Attended baby groups with the selected child Did not attend baby groups Table 5 3 Characteristics associated with response behaviour in the child cohort Characteristics associated with response Characteristics associated with non response Higher income gt 32 000 Lower income or withheld information on income Owner occupiers Rent from a private landlord Live as a couple Lone parent family Used childcare regularly Did not use childcare Respondent suffer poor health Respondent has excellent general health Household is in remote or very remote town Household is in large urban area 5 2 2 Final sweep 2 weights The final sweep 2 weight is the product of the sweep 2 non response weight and the sweep 1 interview weight
12. 06 identifies small area concentrations of multiple deprivation across Scotland It is based on 37 indicators in the seven individual domains of Current Income Employment Health Education Skills and Training Geographic Access to Services including public transport travel times for the first time Housing and a new Crime Domain SIMD 2006 is presented at data zone level enabling small pockets of deprivation to be identified The data zones which have a median population size of 769 are ranked from most deprived 1 to least deprived 6 505 on the overall SIMD and on each of the individual domains The result is a comprehensive picture of relative area deprivation across Scotland The classificatory variable contained in the GUS Sweep 1 datasets is based on the 2006 version of SIMD It should be noted that the analyses in the GUS Sweep 1 report are based on the 2004 version of SIMD as the 2006 version had not been published at the time the report was being written In the dataset the data zones are grouped into quintiles Quintiles are percentiles which divide a distribution into fifths i e the 20th 40th 60th and 80th percentiles Those respondents whose postcode falls into the first quintile are said to live in one of the 20 least deprived areas in Scotland Those whose postcode falls into the fifth quintile are said to live in one of the 20 most deprived areas in Scotland Further details on SIMD can be found on the Scottish Government
13. Mb 3rd new ccare provider hrs per week mbcdyc01 Mb 3rd new ccare provider no of days per week mbcagc01 Mb Age months child started with 3rd new provider MbCwyc01 MbCwyc18 Mb Reasons for using 3 new provider mbctyd01 Mb 4th new provider type mbctmd01 Mb 4th new ccare provider hrs per week mbcdyd01 Mb 4th new ccare provider no of days per week mbcagd01 Mb Age months child started with 4th new provider MbCwyd01 MbCwyd18 Mb Reasons for using 4 new provider DbCnnpo1 Db No of new childcare arrangements in place at sweep 2 Information from the first two sections was used to derive a set of variables forming the third section current arrangements These derived variables indicate for all childcare arrangements in place at the time of the sweep 2 interview the provider type number of hours and days of the arrangement and whether or not it is a new arrangement at sweep 2 A range of summary variables indicating for example use of any childcare total number of providers total hours looked after by all providers and use of different provision are also included These variables are detailed in Table 6 4 15User Guide 15 Table 6 4 Variables for exploring new current childcare arrangements at sweep 2 Variable name Description DbCtot0 1 DbCtya01 Sw2 Childcare provider A provider type DbCnwa Is Provider A a new or existing arrangement DbCtma01 Db Provider A No of hours child looked after per
14. UK Data Archive Study Number 5760 Growing Up in Scotland Cohort 1 ei Scottish Centre for DY Social Research Growing Up In Scotland Sweep 2 2006 2007 User Guide 1 Overview of the survey Ee ERT EE 1 2 Sample Design insis 1 3 Development and Piloting 2 Data colleccion Method iiiad aa aAa a iaa 3 2 Mede of TE 3 Parag Welate We ele 4 255 MMG O Ee OT 4 ele EE A 3 Response fates iiciin aa a aa 4 A Goding and CCUG E 6 5 Ee dee the E EE 6 5 1 Background wide souk SE 6 5 2 Main interview an SEN 6 521 Oe Lol fe MNS TEE 6 5 22 Final sweep 2 weights aise aadanedbdehenadithenadesmcrsesdcassiecsece 8 3 Partner Weights csscssrseseesenees on E E E TT 8 5 3 1 Weighting method ais aiscsscasccenansthensddzmcesccdoavsaansadsd 8 5 3 2 Final partner weights EE 9 5 4 Sample efficiency n ae SEET 9 5 5 Applying the weights vn 10 5 5 1 Main interview weights ai Sos 10 6 5 2 WEE EE 10 EC Usmo the data renra a aA REAA EA IEE 10 Et Ee lee eanan AAR SaN RS 10 62 Valable namng convenio ET 11 Br e leegen E A 11 CA PIS TIV SGV Al Ee 11 Een EELER EE 13 eege EE 13 EE Childcare and Pre school arrangements Au 16 eet SUMMARY VARIA OS Ae EENEG des 18 6 74 Socio economic Characteristics National Statistics Socio economic Classification NS SEC 18 6 7 2 Area level variables Scottish Government Urban Rural Classification ccccccssseeeeseees 18 6 7 3 Area level va
15. Website http Awww scotland gov uk T opics Statistics SIMD Overview 6 7 4 Child Development Communication and Symbolic Behaviour Scale Infant Toddler Checklist Within the self completion section of the interview respondents had to complete questions which assessed their child s communication emotional development understanding and interaction with peers Questions for parents in the birth cohort form the Infant Toddler checklist of the Communication and Symbolic Behaviour CSBS Wetherby and Prizant 2001 The 24 questions are grouped into categories called clusters The items in each cluster can be totalled to yield seven individual cluster scores Results from the clusters are then used to produce three composite scores each assessing different aspects of the child s development social communication expressive speech language and symbolic functioning A total score can also be calculated by summing the three composite scores Those children who score below a certain level on the scale are considered to be of concern in relation to their development As well as containing the constituent items the dataset also includes a set of derived variables including the various composite scores and total score Details of these variables are included in Table 6 2 Corresponding syntax is detailed in the derived variable documentation which accompanies this User Guide 19User Guide 19 Table 6 3 Derived variables associated wit
16. ax to create the combined main interview weight is included below Compute DbWTbrch DbWTorth If SampType 2 DoWTbrch DDWTchid 22User Guide 22 6 10 Missing values conventions 1 Not applicable Used to signify that a particular variable did not apply to a given respondent usually because of internal routing 8 Don t know Can t say 9 No answer Refused These conventions have also been applied to most of the derived variables The derived variable specifications should be consulted for details 7 Documentation The documentation has been organised into the following sections e Survey materials containing interviewer and coding instructions e Data documentation containing the questionnaires main interview and partner with variable names added the list of variables in the dataset including derived variables and a separate list of derived variables with their SPSS syntax 8 Related publications Further information about GUS Sweep 2 is available in Bradshaw P Cunningham Burley S Dobbie F McGregor A Marryat L Ormston R and Wasoff F 2008 Growing Up in Scotland Sweep 2 Overview Report Edinburgh The Scottish Government Other publications which include the use of GUS data include Anderson S Bradshaw P Cunningham Burley S Hayes F Jamieson L McGregor A Marryat L and Wasoff F 2007 Growing Up in Scotland Sweep 1 Overview Report Edinburgh The Scottish Executive Bradshaw P with Jamieson L a
17. dardized versions of the scales z scores can be combined to produce a single scale measuring evidence of negative emotional symptoms in the respondent The constituent items and the derived scale variables are detailed in Table 6 4 below Syntax for compiling the derived variables is detailed in the derived variables documentation Table 6 4 Constituent and derived variables associated with the Depression Anxiety and Stress scale Variable name Description MbHdas01 found myself getting upset by quite trivial things stress MbHdas02 found it difficult to relax stress MbHdas03 felt that had nothing to look forward to depression MbHdas04 felt sad and depressed depression MbHdas05 found that was very irritable stress MbHdas06 was unable to become enthusiastic about anything depression DbHdas01 DASS Raw Stress Score DbHdas02 DASS Raw Depression Score 0 9 ZDbHdas01 Standardised DASS Stress Score ZDbHdas02 Standardised DASS Depression Score DbHdas03 Composite DASS score Further information on DASS is available at http Awwwe2 psy unsw edu au groups dass 6 8 Dropped Variables All variables in the questionnaire documentation with not in dataset next to their name have been deleted from the archived dataset or have been recorded in multiple variables instead The following types of variables specified below have been deleted or replace with a derived variable coded in
18. e in the sweep 2 questionnaire which accompanies this user guide 6 6 1 Childcare and Pre school arrangements At the time of the sweep 2 interview children in the child cohort were aged just under 4 years old At this age children in Scotland are eligible for funded pre school places in private and education authority run nursery classes nursery schools and playgroups As such a module on the transition to and early experiences of pre school was included in the questionnaire for parents in the child cohort The pre school module collected only broad details about the actual provision questions in the childcare section which encompassed pre school would collect more precise information on the provider type the number of hours and the number of days However it became clear on analysis that a number of parents whose children were attending pre school had not provided those pre school details in the childcare section The exclusion of these pre school arrangements from the childcare data meant that data on the proportion of parents using childcare the number of providers being used the mix of provision and the total number of hours was inaccurate in that it missed the pre school arrangement 16User Guide 16 To resolve this a number of derived variables have been created which incorporate information from the pre school module and create more a more accurate picture of current childcare use amongst parents These variables are listed in Tab
19. e and sample efficiency Birth cohort Child cohort Respondent Partner weights Respondent Partner weights weights weights Minimum weight 0 72 0 66 0 67 0 63 Mean weight 1 00 1 00 1 00 1 00 Maximum weight 1 84 2 55 1 80 2 06 Effective sample size 4 293 2 809 2 389 1 478 Sample efficiency 95 94 96 96 Unweighted sample 4 511 2 979 2 500 1 543 size 5 5 Applying the weights 5 5 1 Main interview weights These weights should be used for all analyses of sweep 2 interview data including analysis of combined sweep 1 and sweep 2 data They should not be used for analysis of data from the partner interview 5 5 2 Partner weights These weights should be used for all analysis of data from the partner interview The purpose of the weights is to make the responding partners representative of all partners in the responding households at sweep 2 6 Using the data The GUS Sweep 1 data consists of two SPSS files GUS_SW2Bsav 412 cases GUS _SW2_C sav 2500 cases Child cohort 6 1 Variables on the files Each of the data files contain questionnaire variables excluding variables used for administrative purposes and derived variables The variables included in the file are detailed in the Variable List document in the data section of the documentation As far as possible they are grouped in the order they were asked in the interview 10User Guide 10 6 2 Variable naming convention
20. e time of first interview whereas children in the child cohort were aged around 34 months Weights for the birth and child cohorts have been generated separately since these two groups should always be analysed separately e The Sweep 2 interview follows up all mothers who responded at the first interview and gave ScotCen permission to be re contacted There was no sub sampling Response rates were good at 87 for the birth cohort and 88 for the child cohort e At Sweep 2 we also carried out interviews of any resident partners of the main respondent proxy interviews were not permitted Response rates for the partner interviews were 79 of all couple households in the birth cohort and 77 for the child cohort 5 2 Main interview 5 2 1 Weighting method Unlike the sweep 1 weights a model based weighting technique was used at sweep 2 All cases which were issued at sweep 2 were respondents who had taken part in the sweep 1 interview Information on the sweep 2 non respondents taken from their sweep 1 interview could be used to model their response behaviour at sweep 2 Ineligible households deadwood were not included in the non response modelling Non response behaviour was modelled using logistic regression This is a method of analysing the relationship between an outcome variable in this case response to the sweep 2 interview using a set of predictor variables The model takes account of the relationship of the predictor variables to t
21. er relationship problems and pro social behaviour A score is calculated for each aspect as well as an overall difficulties score which is generated by summing the scores from all the scales except pro social For all scales except pro social where the reverse is true a higher score indicates greater evidence of difficulties The dataset includes the constituent items and the derived variables including the various composite scores and total score Details of these variables are included in Table 6 4 with syntax illustrated in the derived variables documentation Table 6 4 Derived variables associated with the Strengths and Difficulties Questionnaire Variable name Description DbDsdem1 SDQ Emotional symptoms score DbDsdcot SDQ Conduct problems score DbDsdhy1 SDQ Hyper activity or inattention score DbDsdpr1 SDQ Peer problems score DbDsdps1 SDQ Pro social score DbDsdto1 SDQ Total difficulties score Further details on the SDQ can be found at http Awww sdginfo com 20User Guide 20 6 7 6 Parental Health Depression Anxiety and Stress Scale Six items from the Depression Anxiety and Stress DASS scale Lovibond amp Lovibond 1995 were included in the self completion section of the interview DASS is available in a 42 item or 21 item scale in full We took 6 items 3 measuring stress and 3 measuring depression These items can be combined to create a stress scale and depression scale Stan
22. erview Base is all households with an eligible partner in the child cohort n 1 998 R squared Cox and Snells 0 021 28User Guide 28
23. h the CSBS Infant Toddler Checklist Variable name Description DbDcsc01 CSBS Cluster 1 Emotion and eye gaze DbDcsc02 CSBS Cluster 2 Score Communication DbDcsc03 CSBS Cluster 3 Gestures DbDcsc04 CSBS Cluster 4 Sounds DbDcsc05 CSBS Cluster 5 Words DbDcsc06 CSBS Cluster 6 Understanding DbDcsc07 CSBS Cluster 7 Object Use DbDcesc1 1 CSBS Social Composite Score 0 26 DbDesc12 CSBS Speech Composite Score 0 14 DbDcsc13 CSBS Symbolic Composite Score 0 17 DbDcsc20 CSBS Total Score 0 57 DbDcsc21 CSBS Whether child is in concern or no concern range for social composite DbDecsc22 CSBS Whether child is in concern or no concern range for speech composite DbDecsc23 CSBS Whether child is in concern or no concern range for symbolic composite DbDcsc30 CSBS Whether child is in concern or no concern range for overall measure Further details on the CSBS can be found at http Awww brookespublishing com store books wetherby csbsdp index htm checklist 6 7 5 Child Development Strengths and Difficulties Questionnaire Parents in the child cohort completed the Strengths and Difficulties Questionnaire SDQ The SDQ is a brief behavioural screening questionnaire designed for use with 3 16 year olds The scale includes 25 questions which are used to measure five aspects of the child s development emotional symptoms conduct problems hyperactivity inattention pe
24. he outcome and the relationships of the predictor variables to each other To speed up the modelling process a bivariate analysis was carried out prior to the modelling to identify variables that were related to response behaviour The variables included in the shortlist are listed in table 5 1 2 Further information on the sample design and the weighting process at sweep 1 can be found in the Sweep 1 User Guide which is available from the Data Archive SN 5760 or the using GUS data section of the Growing Up in Scotland website www growingupinscotland org uk 3 There were 45 individuals with ineligible outcome codes these individuals were dropped from the 6User Guide 6 Table 5 1 Variables used in non response model Variable Name Description DaHGnp04 Whether respondent is living with spouse partner DaHGprim Whether cohort child was mother s first born amongst children in household MaWinc09 Household income DaMedu03 Highest Education level of Mother DaEthGpM Ethnicity of Respondent DaMsta01 Respondents employment status DaMsta10 Household employment status MaZhou05 Tenure DaHGnmkd Number of children in household DaHGag2 Respondent s age at time of interview DaHGmr2 Respondent s marital status DaURind1 ONS Urban Rural indicator Scotland DaADsco02 Scottish Index of Multiple Deprivation data zone level 2004 Quintiles MaCany01 Respondent
25. hild dates of birth for inclusion in the Growing Up in Scotland study by cohort Sample Dates of Birth required Number Birth Cohort Child Cohort 1 01 June 2004 30 Jun 2004 01 June 2002 30 Jun 2002 2 01 Jul 2004 31 Jul 2004 01 Jul 2002 31 Jul 2002 3 01 Aug 2004 31 Aug 2004 01 Aug 2002 31 Aug 2002 4 01 Sep 2004 30 Sep 2004 01 Sep 2002 30 Sep 2002 5 01 Oct 2004 31 Oct 2004 01 Oct 2002 31 Oct 2002 6 01 Nov 2004 30 Nov 2004 01 Nov 2002 30 Nov 2002 7 01 Dec 2004 31 Dec 2004 01 Dec 2002 31 Dec 2002 8 01 Jan 2005 31 Jan 2005 01 Jan 2003 31 Jan 2003 9 01 Feb 2005 28 Feb 2005 01 Feb 2003 28 Feb 2003 10 01 Mar 2005 31 Mar 2005 01 Mar 2003 31 Mar 2003 11 01 Apr 2005 30 Apr 2005 01 Apr 2003 30 Apr 2003 12 01 May 2005 31 May 2005 01 May 2003 31 May 2003 LA Development and Piloting Policy priorities and key topics of interest for the sweep 2 questionnaire were initially discussed and agreed by the study s Scottish Government Project Managers and Policy Advisory Group The questionnaire was then developed by the GUS team at ScotCen with input from colleagues at the Centre for Research on Families and Relationships in reference to these priorities and topics A subset of new questions was included in a small cognitive pilot in September 2005 with a full instrument initially piloted in paper form in November 2005 This instrument was revised and converted into CAPI for the second Dress Rehearsal
26. ible for sweep 2 in the child cohort n 2 845 R squared Cox and Snells 0 047 26User Guide 26 Table A3 Full model for non response to the partner interview birth cohort H Wad d Highest Education level of Respondent SE Sig Exp B Banded 23 4 2 0 000 Higher or above 0 57 0 15 13 6 1 0 000 1 77 Standard grade or other 0 15 0 17 0 8 1 0 366 1 17 No qualifications baseline Mothers employment status 27 8 2 0 000 Child s mother working full time 0 96 0 18 27 2 1 0 000 2 60 Child s mother working part time 0 40 0 13 8 9 1 0 003 1 49 Child s mother not working baseline Household employment and family type 27 2 2 0 000 Couple family both mother and partner working gt 16 hours 1 23 0 24 27 2 1 0 000 0 29 Couple family either mother or partner working gt 16 hours 0 86 0 20 18 4 1 0 000 0 42 Couple family both unemployed or lt 16 hours baseline Ethnicity of Child 8 9 1 0 003 White 0 50 0 17 8 9 1 0 003 1 64 Other ethnic background baseline Age of mother at birth of sample child banded 14 3 3 0 003 Under 20 0 40 0 32 1 6 1 0 209 0 67 20 to 29 0 40 0 24 2 9 1 0 088 0 67 30 to 39 0 08 0 23 0 1 1 0 720 0 92 40 or older baseline Whether first time Primaporous mother 15 7 1 0 000 Primiparous 0 35 0 09 15 7 1 0 000 1 42 Other children baseline Constant 1 10 0 34 10 4 1 0 001 3 00 Notes Outcome is 1 partner gave an interview 0 no partner interview Base is all househ
27. ieldwork was undertaken over a fourteen month period commencing in April 2006 The sample was issued in twelve monthly waves at the beginning of each month and each month s sample was in field for a maximum period of two and a half months For example sample 2 was issued at the beginning of May 2006 and remained in field until mid July 2006 To ensure that respondents in both samples were interviewed when their children were approximately the same age each case was assigned a target interview date For the birth cohort this was identified as the date on which the child turned 22 5 months old and for the child cohort the date the child turned 46 5 months old Interviewers were allotted a four week period based on this date two weeks either side in which to secure the interview In difficult cases this period was extended up to and including the child s subsequent birthday which allowed a further four weeks The vast majority of interviews were achieved within the four week target period 2 4 Partner interviews As well as the main interview at sweep 2 CAPI interviews were also undertaken with the resident partner of the main respondent Given that in the vast majority of cases the main respondent was the child s natural mother most of the partner interviews 97 were conducted with the child s natural father The partner s interview was shorter than and used a selection of questions from the main interview A total of 2 975 part
28. le 6 5 Table 6 5 Childcare variables including a correction for the excluded pre school cases Variable name Description DbCany02 Whether or not using childcare including those who had excluded pre school arrangements DbCtot02 Number of childcare providers being used at sw2 including previously excluded pre school arrgts DbCtyf01 Sw2 Childcare provider E derived provider type for those who did not provide pre school details in childcare section DbCimf01 No of hours looked after per week by provider F excluded pre school provider DbCdyf01 No of days looked after per week by provider F excluded pre school provider DbCtmi01 Db Total number of hours child is currently looked after by someone else in an average week DbCimi02 Db Total number of hours child is currently looked after by someone else in an average week BANDED DbCday01 Db Highest number of days child is in any one childcare arrangement DbCtyp01 Db Does respondent use grandparents for childcare DbCtyp02 Db Does respondent use another relative for childcare DbCtyp03 Db Does respondent use private creche nursery for childcare DbCtyp04 Db Does respondent use a childminder for childcare DbCtyp05 Db Does respondent use a local authority playgroup for childcare DbCtyp06 Db Does respondent use a local authority nursery for childcare DbCtyp07 Db Does respondent use a private playgroup for childcare DbCtyp08 Db Does respondent use a community voluntary
29. nd Wasoff F 2008 Use of informal support by families with young children Edinburgh Scottish Government Bradshaw P and Martin C with Cunningham Burley S 2008 Exploring the experience and outcomes for advantaged and disadvantaged families Edinburgh Scottish Government Jamieson L with Ormston R and Bradshaw P 2008 Growing Up in Rural Scotland Edinburgh Scottish Government Skafida V 2008 Breastfeeding in Scotland The impact of advice for mothers Centre for Research on Families and Relationships Briefing 36 February 2008 Edinburgh Centre for Research on Families and Relationships 23User Guide 23 These reports and other related information are available on the GUS website http www growingupinscotland org uk 9 Contact details Contacts at the Scottish Centre for Social Research 73 Lothian Road Edinburgh EH3 9AW GUS Project Manager Paul Bradshaw 0131 228 2167 p bradshaw scotcen org uk GUS Data Manager Joan Corbett 0131 221 2560 j corbett scotcen org uk 10 References Goodman R 1997 The Strengths and Difficulties Questionnaire A Research Note Journal of Child Psychology and Psychiatry 38 581 586 Lovibond S H amp Lovibond P F 1995 Manual for the Depression Anxiety Stress Scales 2nd Ed Sydney Psychology Foundation Wetherby A M and Prizant B M 2001 Communication and Symbolic Behaviour Scales Infant Toddler Checklist Baltimore Paul H Brookes Publishing Co
30. ndom The Department of Work and Pensions then sampled children from these 130 sample points Within each sample point the Child Benefit records were used to identify all babies and three fifths of toddlers who met the date of birth criteria see Table 1 2 The sampling of children was carried out on a month by month basis in order to ensure that the sample was as complete and accurate as possible at time of interview In cases where there was more than one eligible child in the selected household one child was selected at random If the children were twins they had an equal chance of being selected If the eligible children were in different age cohorts the younger child had a higher chance of being selected given that those children had a higher chance of being included in the sample overall After selecting the eligible children the DWP made a number of exclusions before transferring the sample details These exclusions included cases they considered sensitive and children that had been sampled for research by the DWP in the last 3 years 1 Local Authority has been used as a stratification variable during sampling this means the distribution of the GUS sample by Local Authority will be representative of the distribution of Local Authorities in Scotland However the sample sizes are such that we would not recommend analysis by Local Authority The small sample sizes would give misleading results 2User Guide 2 Table 1 2 Eligible c
31. ner interviews were successfully completed in the birth cohort and 1 541 in the child cohort These figures represent response rates of 79 and 77 respectively 3 Response rates Details of the number of cases issued and achieved and the response rates are detailed in Table 3 1 4User Guide 4 Table 3 1 Number of issued and achieved cases and response rates Birth Child All Sample All eligible children No of sweep 1 achieved interviews 5217 2858 8075 Cases to field All 5217 2858 8075 Achievable or in scope 5158 2822 7980 Cases achieved 4512 2500 7012 Response rate As of all sweep 1 cases 87 88 87 As of all in scope 88 89 88 Cases which were considered out of scope or unachievable were mostly ineligible addresses usually due to the family having moved away from Scotland 5User Guide 4 Coding and editing Additional coding and editing tasks were performed after the interviews were conducted The GUS Sweep 2 Coding Instructions provide details of the tasks that were conducted 5 Weighting the data 5 1 Background e The sampling frame was the child level Child Benefit records held by the Inland Revenue Children were selected from 120 sample points in Scotland The sample points consist of aggregations of Data Zones e There are two cohorts of children the birth cohort and child cohort Children in the birth cohort were aged approximately 10 months at th
32. olds with an eligible partner in the birth cohort n 3 764 R squared Cox and Snells 0 032 27User Guide 27 Table A4 Full model for non response to the partner interview child cohort B S E WELS df Sig Exp B ONS Urban Rural indicator Scotland 12 3 5 0 031 Large urban area 125 000 0 31 0 29 1 2 1 0 283 0 73 Other urban area 10 000 125 000 0 55 0 29 3 7 1 0 053 0 57 Accessible small town 3 000 10 000 0 34 0 32 1 1 1 0 290 0 71 Remote and very remote small town 1 06 0 39 7 2 1 0 007 0 35 3 000 10 000 Accessible rural lt 3 000 0 61 0 30 4 1 1 0 042 0 54 Remote and very remote rural lt 3 000 baseline Mothers employment status 16 8 2 0 000 Child s mother working full time 0 91 0 23 16 1 1 0 000 2 49 Child s mother working part time 0 62 0 18 11 9 1 0 001 1 86 Child s mother not working baseline Household employment and family type 13 0 2 0 001 Couple family both mother and partner 1 03 0 33 10 0 1 0 002 0 36 working gt 16 hours Couple family either mother or partner 0 51 0 29 3 2 1 0 076 0 60 working gt 16 hours Couple family both unemployed or lt 16 baseline hours Ethnicity of Child 3 8 1 0 052 White 0 47 0 24 3 8 1 0 052 1 60 Other ethnic background baseline Whether first time Primaporous mother 5 1 1 0 024 Primiparous 0 25 0 11 5 1 1 0 024 1 29 Other children baseline Constant 1 41 0 44 10 1 1 0 001 4 11 Notes Outcome is 1 partner gave an interview 0 no partner int
33. ortion of 2 3 year olds are living in single parent families in 2005 2 Cross sectional time series data e g is there any change in the proportion of 2 3 year olds living in single parent families between 2005 and 2007 3 Longitudinal cohort data e g what proportion of children who were living in single parent households aged 2 3 are living in different family circumstances at age 4 5 1 2 Sample Design The area level sampling frame was created by aggregating Data Zones Data Zones are small geographical output areas created for the Scottish Government Data Zones are used to release data from the Census 2001 are used by Scottish Neighbourhood Statistics to release small area statistics The Data Zone geography covers the whole of Scotland The geography is hierarchical with Data Zones nested within Local Authority boundaries Each data zone contains between 500 and 1 000 household residents More information can be found on the Scottish Neighbourhood Statistics website http Awww sns gov uk The Data Zones were aggregated to give an average of 57 births per area per year based on the average number of births in each Data Zone for the preceding 3 years It was estimated that this number per area would provide us with the required sample size Once the merging task was complete the list of aggregated areas was sorted by Local Authority and then by the Scottish Index of Multiple Deprivation Score 130 areas were then selected at ra
34. playgroup for childcare DbCtyp09 Db Does respondent use an ex spouse or partner for childcare DbCtyp10 Db Does respondent use the childs older sibling for childcare DbCtyp11 Db Does respondent use a friend or neighbour for childcare DbCtyp12 Db Does respondent use a daily visiting nanny for childcare DbCtyp13 Db Does respondent use a live in nanny for childcare DbCtyp14 Db Does respondent use a babysitter for childcare DbCtyp15 Db Does respondent use a workplace creche or nursery for childcare DbCtyp16 Db Does respondent use a family centre for childcare DbCtyp17 Db Does respondent use a nursery class attached to a primary school for childcare DbCtyp18 Db Does respondent use a childcarer provided via childcare agency for childcare DbCtyp19 Db Does respondent use another type of childcare provider for childcare DbCtyp20 Db Does respondent currently use OTHER INFORMAL childcare DbCtyp21 Db Does respondent currently use NURSERY OR CRECHE for childcare DbCtyp22 Db Does respondent currently use PLAYGROUP for childcare DbCtyp23 Db Does respondent currently use OTHER PROVIDERS for childcare DbCtyp30 Db Does respondent currently use informal childcare DbCtyp31 Db Does respondent currently use formal childcare DbCtyp32 Db Current use of formal and informal childcare 17User Guide 6 7 Indicators and summary variables 6 7 1 Socio economic Characteristics National Statistics Socio economic Classification NS SEC
35. riables Scottish Index of Multiple Deprivation cee eeeeceeeeeeeeeeeteeeeeeneeeeeeaees 19 6 7 4 Child Development Communication and Symbolic Behaviour Scale Infant Toddler Checklist19 6 7 5 Child Development Strengths and Difficulties Ouestonnalre ceceeeeeteeeteeeeeeteteeeeeeeeee 20 6 7 6 Parental Health Depression Anxiety and Stress Scale AER 21 1 Dropped EE 21 HES VV IGM GE EE 22 BAO MISSING VAISS CONVE MIIONS EE 23 7 Borurmertattuett eege tee 23 8 Related eeleren x scc acct scccs sete aa aa aaa aaa 23 9 G ntact EU 24 10 Ree erte 24 Appendix A Full non response Models cccsccceseesseeeeseeeeeeeeeseeeseseeeenseneeseeeseseaesnsneeeeees 25 1 Overview of the survey The data files contain data from Growing Up in Scotland GUS Sweep 2 the second year of a longitudinal research study aimed at tracking the lives of a cohort of Scottish children from the early years through childhood and beyond Funded by the Scottish Government Education Directorate its principal aim is to provide information to support policy making but it is also intended to be a broader resource for secondary analysis The aims of the study are e To provide reliable cross sectional data on the characteristics circumstances and experiences of children in Scotland aged between 0 and 5 e To document differences in the current characteristics circumstances and experiences of children from different backgrounds e To generate info
36. rmation about longer term outcomes across a range of key domains and to document differences in those outcomes for children of different backgrounds e To identify key predictors of adverse longer term outcomes with particular reference to the role of early years service provision e To measure levels of awareness and use of key services e To examine the nature and extent of informal sources of help advice and support for parents e To generate parental assessments of the services accessed and used and to improve understandings of choice and constraint in service use 1 1 Study Design The survey is based on two cohorts of children the first aged approximately 10 months at the time of first interview and the second aged approximately 34 months A named sample of approximately 10 700 children was selected from the Child Benefit records to give an achieved sample of 8 000 overall The configuration of cohorts and sweeps for the first four sweeps of data collection is summarised below BC1 refers to the younger of the two cohorts birth cohort and CC1 to the slightly older cohort child cohort Table 1 1 Proposed sample design 2005 2011 1User Guide Age at interview Year 0 1 1 2 2 3 3 4 4 5 5 6 2005 BC1 CC1 2006 BC1 CC1 2007 BC1 CC1 2008 BC1 CC1 A key aim of using two cohorts is to allow the study to provide three types of data 1 Cross sectional time specific data e g what prop
37. rovider type MaCtme01 Sw1 5th childcare provider no of hours per week MaCdye01 Sw1 5th childcare provider no of days per week MbCsta01 Mb Whether still using 1st provider from sweep 1 MbCcta01 Swi 1st ccare provider revised hrs at sw2 MbCcda01 Sw1 1st ccare provider revised days at sw2 MbCrsa01 Main reason no longer using provider 1 from sw1 at sw2 MbCstb01 Mb Whether still using 2nd provider from sweep 1 MbCctbo1 Swi 2nd ccare provider revised hrs at sw2 MbCcdb01 Swi 2nd ccare provider revised days at sw2 MbCrsb01 Main reason no longer using provider 2 from sw1 at sw2 MbCstc01 Mb Whether still using 3rd provider from sweep 1 MbCctc01 Swi 3rd ccare provider revised hrs at sw2 MbCcdc01 Sw1 3rd ccare provider revised days at sw2 MbCrsc01 Main reason no longer using provider 3 from sw1 at sw2 MbCstd01 Mb Whether still using 4th provider from sweep 1 MbCctd01 Sw1 4th ccare provider revised hrs at sw2 MbCcdd01 Sw1 4th ccare provider revised days at sw2 MbCrsd01 Main reason no longer using provider 4 from sw1 at sw2 MbCste01 Mb Whether still using 5th provider from sweep 1 MbCcte01 Sw1 5th ccare provider revised hrs at sw2 MbCcde01 Sw1 5th ccare provider revised days at sw2 MbCrse01 Main reason no longer using provider 5 from sw1 at sw2 DbCstp01 Db Has respondent stopped using any of the childcare arrangements they were using at sweep 1 DbCstp02 Db How many of the childcare arrangements they were using a
38. s which were in place at sweep 2 but had not been in place at sweep 1 The multiple sets of information collected create a particularly complex data structure 13User Guide 13 To make this complex picture more comprehensible the childcare data can be usefully separated into three sections suitable for different types of analysis The first is concerned with continuity of provision from sweep to sweep The relevant variables include those which contain the details of sweep 1 childcare arrangements and those which confirm whether or not the arrangement is still in place and for those arrangements which have been ceased the reasons why These variables are detailed in Table 6 2 Table 6 2 Childcare variables for exploring continuity of provision Variable name Description MaCtya01 Sw1 1st childcare provider type MaCtma01 Sw1 1st childcare provider no of hours per week MaCdya01 Sw1 1st childcare provider no of days per week MaCtyb01 Sw1 2nd childcare provider type MaCtmb01 Sw1 2nd childcare provider no of hours per week MaCdyb01 Sw1 2nd childcare provider no of days per week MaCtyc01 Sw1 3rd childcare provider type MaCtmc01 Sw1 3rd childcare provider no of hours per week MaCdyc01 Sw1 3rd childcare provider no of days per week MaCtyd01 Sw1 4th childcare provider type MaCtmd01 Sw1 4th childcare provider no of hours per week MaCdyd01 Sw1 4th childcare provider no of days per week MaCtye01 Sw1 5th childcare p
39. squared Cox and Snells 0 052 25User Guide 25 Table A2 Full model for non response to sweep 2 interview child cohort Variables in the Equation B S E ET Ke df Sig Exp B Tenure 16 2 2 0 00 Owner occupier 0 74 0 20 14 0 1 0 00 2 11 Rents HA council 0 24 0 19 1 6 1 0 20 1 27 Rents private baseline Household income 18 0 4 0 00 Less than 9 999 baseline 10 000 19 999 0 18 0 18 1 1 1 0 31 0 83 20 000 31 999 0 05 0 23 0 0 1 0 84 0 96 32 000 or more 0 25 0 24 1 1 1 0 29 1 29 Missing 0 59 0 22 7 4 1 0 01 0 56 Respondent regularly uses childcare 13 4 1 0 00 Yes 0 47 0 13 13 4 1 0 00 1 60 No baseline Family type 8 4 1 0 00 Lone parent family 0 46 0 16 8 4 1 0 00 0 63 Couple family baseline Respondent s general health 10 5 3 0 02 Excellent 0 53 0 20 6 9 1 0 01 0 59 Very good 0 05 0 18 0 1 1 0 76 0 95 Good 0 29 0 18 2 6 1 0 11 0 75 Fair poor baseline ONS Urban Rural indicator Scotland 13 8 5 0 02 Large urban area 125 000 0 91 0 38 5 8 1 0 02 0 40 Other urban area 10 000 125 000 0 60 0 38 2 5 1 0 12 0 55 Accessible small town 3 000 10 000 0 54 0 41 1 8 1 0 19 0 58 Remote and very remote small town 0 07 0 58 0 0 1 0 90 1 07 3 000 10 000 Accessible rural lt 3 000 0 62 0 40 2 4 1 0 12 0 54 Remote and very remote rural lt 3 000 baseline Constant 1 61 0 44 13 4 1 0 00 5 02 Notes Outcome is 1 respondent gave a sweep 2 interview 0 no sweep 2 interview Base is all households elig
40. t sweep 1 14User Guide has the respondent stopped using DbCnpv01 Db Number of childcare provs from sweep 1 still being used DbCapv01 Is respondent still using a childcare provider that had been used at sweep 1 The second section is concerned with the details of new arrangements which were in place at sweep 2 These variables include details of the provider type the number of hours and days per week they look after the child the child s age when the arrangement commenced and the reasons given for using the provision Details of the variables are listed in Table 6 3 Table 6 3 Variables for exploring new childcare arrangements at sweep 2 Variable name Description MbCany02 Mb Whether using any childcare those who had no childcare at sw1 MbCany03 Mb Whether using any new childcare arrangements those who were using childcare at sw1 Mbctya01 Mb 1st new provider type Mbctma01 Mb 1st new ccare provider hrs per week Mbcdya01 Mb 1st new ccare provider no of days per week Mbcaga01 Mb Age months child started with 1st new provider MbCwya01 MbCwya18s Mb Reasons for using 1 new provider Mbctyb01 Mb 2nd new provider type Mbctmb01 Mb 2nd new ccare provider hrs per week Mbcdyb01 Mb 2nd new ccare provider no of days per week Mbcagb01 Mb Age months child started with 2nd new provider MbCwyb01 MbCwyb18 Mb Reasons for using 2 new provider mbctyc01 Mb 3rd new provider type mbctmc01
41. times from settlements of 10 000 or more people The definitions of urban and rural areas underlying the classification are unchanged The classification has been designed to be simple and easy to understand and apply It distinguishes between urban rural and remote areas within Scotland and includes the following categories Table 6 2 Scottish Government Urban Rural Classification Classification Description 1 Large Urban Areas Settlements of over 125 000 people 2 Other Urban Areas Settlements of 10 000 to 125 000 people 3 Accessible Small Towns Settlements of between 3 000 and 10 000 people and within 30 minutes drive of a settlement of 10 000 or more 4 Remote Small Towns Settlements of between 3 000 and 10 000 people and with a drive time of over 30 minutes to a settlement of 10 000 or more 5 Accessible Rural Settlements of less than 3 000 people and within 30 minutes drive of a settlement of 10 000 or more 6 Remote Rural Settlements of less than 3 000 people and with a drive time of over 30 minutes to a settlement of 10 000 or more For further details on the classification see Scottish Executive 2004 Scottish Executive Urban Rural Classification 2003 2004 This document is available online at http www scotland gov uk Publications 2004 06 19498 38784 18User Guide 18 6 7 3 Area level variables Scottish Index of Multiple Deprivation The Scottish Index of Multiple Deprivation SIMD 20
42. to broader categories in order to reduce the potential to identify individuals 1 Those containing text 2 Those which contained a personal identifier e g name address 3 Those considered to be disclosive such as e Detailed ethnicity e Specific country of birth e Language spoken at home e Full interview date e Full date of birth e Timing variables There are no geographical variables in the archived dataset beyond area urban rural classification and Scottish index of multiple deprivation summary variable 21 User Guide 21 6 9 Weighting variables The final main interview sweep 2 weights are DbWTbrth birth cohort and DbWTchld Child cohort The partner weights are DbWtBrtP bith cohort and DbWtchllP child cohort Separate weights are provided for each cohort because analysis should always treat each cohort as a distinct population However key analysis using this data may involve comparison between the cohorts It is usually more convenient to undertake this analysis by combining the two cohort datasets into a single dataset and then ensuring that subsequent analysis is either filtered to select a single cohort or that output is nested by cohort type SampType On merging the datasets it is possible to create a combined weight variable in order that nested analysis uses just a single weight variable The value of the combined weight is equal to the value of the corresponding cohort weight variable for that child Synt
43. week DbCdya01 Db Provider A No of days child looked after per week DbCtyb01 Sw2 Childcare provider B provider type DbCnwb Is Provider B a new or existing arrangement DbCtmb01 Db Provider B No of hours child looked after per week DbCdyb01 Db Provider B No of days child looked after per week DbCtyc01 Sw2 Childcare provider C provider type DbCnwc Is Provider C a new or existing arrangement DbCtmc01 Db Provider C No of hours child looked after per week DbCdyc01 Db Provider C No of days child looked after per week DbCtyd01 Sw2 Childcare provider D provider type DbCnwd Is Provider D a new or existing arrangement DbCtmd01 Db Provider D No of hours child looked after per week DbCdyd01 Db Provider D No of days child looked after per week DbCtye01 Sw2 Childcare provider E provider type DbCnwe Is Provider E a new or existing arrangement DbCtme01 Db Provider E No of hours child looked after per week DbCdye01 Db Provider E No of days child looked after per week DbCany01 Db Does respondent currently get help with childcare for childname on a regular basis not including the excluded pre school cases see 6 6 1 Db Number of childcare providers being used at sweep 2 not including the excluded pre school cases see 6 6 1 Although not listed in Table 6 4 this section also covers variables associated with cost availability choice and preferences Details of these questions and the corresponding variables are availabl
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