Predicting participation in higher education: A comparative evaluation of the performance of geodemographic classifications

Abstract

Summary. Participation in UK higher education is modelled by using Poisson regression techniques. Models using geodemographic classifications of neighbourhoods of varying levels of detail are compared with those using variables that are directly derived from the census, using a cross-validation approach. Increasing the detail of geodemographic classifiers appears to be justified in general, although the degree of improvement becomes more marginal as the level of detail is increased. The census variable approach performs comparably, although it is argued that this depends heavily on an appropriate choice of predictors. The paper concludes by discussing these results in a broader practice-oriented and pedagogic context. © 2011 Royal Statistical Society.