1 Data Linkage for Educational Research Royal Statistical Society March 19th 2007 Andrew Jenkins and Rosalind Levačić Institute of Education, University of London

2 Examples of Data Linkage (1) Data Linkage with the Longitudinal Survey of Young People in England (LSYPE) and the National Pupil Database (NPD) (2) Linking NPD to a survey of student experiences at school for evaluation of Diversity Pathfinders

3 Structure of presentations Introduce the datasets used Outline why data linkage was useful/important How the datasets were combined Any practical problems which arose in linking data Methodological issues in using linked data

4 Main aim of research project (1) To use data from first wave of Longitudinal Survey of Young People in England (LSYPE), combined with other datasets, to try to separate out effects of family background and neighbourhood on students’ attainment.

5 Value of Data Linkage Richer and more detailed models –e.g. Administrative data may include little about pupil background Better control variables –e.g. controlling for family background factors when modelling neighbourhood effects on attainment

6 Datasets to be combined: Pupil Level: LSYPE NPD School Level: Edubase Annual School Census Neighbourhood Level: Area variables from 2001 Census Indices of Deprivation

7 Longitudinal Survey of Young People in England Begins at age 14, in 2004 Annual Interviews until age 25 Currently only wave 1 data available Includes interviews with young person and parent/adult

8 LSYPE variables: some examples. Family Siblings, mother’s education, mother’s occupation, single parent household, state benefits/ tax credit Pupil Attitudes to school, homework, future plans, risk factors e.g. in contact with police, truanting etc... Parent Expectations for child’s education, helping with homework, family joint activities, parent involvement in school

9 Overview of National Pupil Database (NPD) Information on all state school pupils in England Includes national test score results It is longitudinal –Pupils can be tracked through Key Stages NPD includes Pupil Level Annual School Census (PLASC) –PLASC provides pupil background data e.g. ethnicity, SEN NPD owned by DfES who manage access to the data

10 Variables and data. National Pupil Database Pupil level variables Key Stage 3 scores and Key Stage 2 prior attainment in maths, English, science; gender, SEN Family variablesFSM eligibility, ethnicity, EAL

11 Neighbourhood variables. Census area variables (examples) Indices of Deprivation (examples) Proportion unemployedEmployment deprivation score Proportion lone parent households Income deprivation score Proportion with level 1 or lower qualification Skills deprivation score Proportions from various ethnic groups Children’s educational deprivation score

12 Linking pupils and schools DfES provided us with linked LSYPE/NPD data Linkage to school-level data using LEA and Establishment numbers

13 Combining pupil and neighbourhood data National Pupil Database includes pupil postcodes Census data and Indices of Deprivation linked to the National Pupil Database using National Statistics Postcode Directory (NSPD, formerly AFPD) The NSPD provides a look-up between postcodes and various administrative geography codes

14 Some problems in using linked data Reductions in sample size –NPD has approx 0.5 million cases per year –LSYPE has sample size of around 15,000 Missing data Representativeness of data which does link successfully Getting access to linked data

15 Outcomes of data linkage with LSYPE N% Total sample in LSYPE (Wave 1)15, Did not merge with neighbourhood data Did not merge with school data Remaining cases14,

16 Linking a pupil survey to National Pupil Database: Diversity Pathfinders Project Purpose of survey: to collect data as part of a 3.5 year evaluation of Diversity Pathfinders ( ). Six Local Authorities provided with some funding by DfES to promote collaboration between groups of secondary schools with the purpose of raising standard and promoting diversity through attaining specialist status. Largely a qualitative study using interviews and some participant observation, supplemented by an analysis of examination performance and a survey of students’ views and experiences ‘before’ and ‘after’ three years.

17 DP research design Since DP was ‘pathfinding’ it was not a uniform treatment with controls. By intention each LA developed its own approach and own way of selecting and grouping schools for collaboration within the DP project. The research team selected 31 schools as case studies for which evidence collected by interviews. These schools were also the ones selected for a survey. Each school selected one mixed ability Year 11 form to respond to the survey on-line.

18 Purpose of the DP student survey To establish: how did students rate aspects of their learning experience? did students in 2005/6 rate their learning experiences better than those in 2002/3, especially with regard to increased working with students from other schools? did students’ learning experiences differ by school and by student characteristics? did more disadvantaged students have an improved learning experience after 3 years of DP?

19 Use of National Pupil Database NPD provides data on student’s prior attainment (KS2 and KS3) gender ethnicity special educational needs eligibility for free school meals English as an additional language

20 Advantages of data linkage Obtaining data on student characteristics without needing to ask intrusive questions on the survey or extend length of questionnaire; Did not need to use alternative of asking the school to supply the data – would add to burden of survey to schools and reduce further the response rate.

21 Mechanics of achieving data linkage between DP survey and NPD NPD consists of Pupil Level Annual Census plus test results. Each pupil has a Unique Pupil Number (UPN) used by the school when reporting data to DfES. We needed the schools to give us the UPNs of the students in the form doing the survey. Also DoB in case needed for matching. UPNs are highly confidential – letter from DfES to schools requesting this. Problem: getting UPNs out of each school. 28 schools responded in 2002/3: only 16 in 2005/6.

22 How UPNs used Each pupil given a DP project identifier number which was attached to a questionnaire. At school pupil used id number to download own questionnaire. NPD uses matching pupil reference number. We sent UPNs to DfES and they matched with pupil reference number and sent us matched NPD data for these students.

23 Linking UPN, matching pupil reference number and DP survey pupil identity number (example: not actual data)

24 Methodological issues Missing data: from schools that do not supply UPNs due to non matching of UPNs and PMRs due to missing data in NPD. Raises questions about how representative the data are. Inconsistent data between DP survey and NPD- gender in some cases.

25 DP survey: some results using data linkage

26 Advantages of data linkage for DP evaluation Able to compare students from two waves of the survey Able to control for pupil characteristics in analysis of questionnaire responses when comparing years or schools. Able to address research questions on relationship between pupils’ characteristics and experience of school.