Missing Key Stage 2 Data in LSYPE2

The Second Longitudinal Study of Young People in England (LSYPE2) provides a resource for evidence-based policy development. A significant barrier to achieving this purpose could be the missingness present in LSYPE2, owing to a boycott of Key Stage 2 (KS2) testing in 2010. Specifically, in 2010, 15,518 maintained schools were expected to administer KS2 tests, but around one-quarter (4,005 schools; 26 per cent) of these did not administer it. Boycotts of national tests leave gaps in pupils' attainment records and, in the case of LSYPE2, threaten to undermine a large-scale longitudinal study with substantial policy relevance. This project sought to find a way to calculate values for pupils who attended schools that boycotted KS2 tests in 2010 and/or partly mitigate the effect of the boycott on this study. Prior attainment data is something that should be incorporated into even basic analyses of LSYPE2, and so analysts and researchers need to decide whether the missing data arising from the boycott will cause difficulties when they are making inferences and conclusions in their work, and they then need to take appropriate steps to deal with these difficulties if necessary. The results of the analyses undertaken for this project suggest that complete-cases analyses using only pupil-level data that include a random effect for primary sampling unit (i.e. secondary school) should be unbiased. Comparing complete-case analysis with multiple imputation (MI) suggests that MI would be more efficient than the complete-case approach — i.e. standard errors (SE) would be smaller, meaning this approach should be used if statistical inference is the aim of a given analysis. In this report we present an introduction to LSYPE2 and the KS2 Standard Assessment Tests (SATS) boycott in Chapter 1 and to statistical issues with missing data, and to methods for addressing these in Chapter 2. In Chapters 3 and 4 we explore predictors of missing KS2 test scores among LSYPE2 cohort participants, as well as predictors of KS2 attainment. Chapters 6 to 9 describe the methodological approaches and challenges to the MI and inverse probability weighting (IPW) approaches taken. Sensitivity analyses are presented in the appendix to this report. The user guide accompanying this report walks potential users of the imputed/inverse probability weighting variables through descriptive and multivariable analyses. We have taken a pragmatic approach to this work, balancing the need for practical solutions for analysts with the desire to exhaustively explore options for dealing with missingness. This report includes an assessment of the strengths and limitations of the approaches taken, in particular, the assumptions made in the development of the MI data.