Modelling non-response in the National Child Development Study

There is widespread concern that the cumulative effects of the non-response that is bound to affect any long-running longitudinal study will lead to mistaken inferences about change. We focus on the National Child Development Study and show how non-response has accumulated over time. We distinguish between attrition and wave non-response and show how these two kinds of non-response can be related to a set of explanatory variables. We model the discrete time hazard of non-response and also fit a set of multinomial logistic regressions to the probabilities of different kinds of non-response at a particular sweep. We find that the best predictors of non-response at any sweep are generally variables that are measured at the previous sweep but, although non-response is systematic, much of the variation in it remains unexplained by our models. We consider the implications of our results for both design and analysis.