Latent class marginal regression models for modelling youthful drug involvement and its suspected influences

Abstract

In longitudinal behavioural studies, it is common to have multiple categorical indicators for measuring a theoretical construct of interest. A latent class model is presented that accounts for the structure in a set of correlated, categorical variables measured at discrete time periods, drawing information from these variables to form a smaller number of latent classes. The dependence of the resulting latent class model parameters on suspected factors over time is simultaneously modelled using a baseline-category logistic regression model. Estimation of the model parameters is achieved using an estimating equations procedure. A motivating example is provided from a longitudinal study of suspected linkages between monitoring or supervision by parents and the occurrence of drug use behaviours in an epidemiologic sample of school-attending youths.