Latent Class Logistic Regression: Application to Marijuana Use and Attitudes Among High School Seniors

Abstract

SummaryAnalysing the use of marijuana is challenging in part because there is no widely accepted single measure of individual use. Similarly, there is no single response variable that effectively captures attitudes toward its social and moral acceptability. One approach is to view the joint distribution of multiple use and attitude indicators as a mixture of latent classes. Pooling items from the annual ‘Monitoring the future’ surveys of American high school seniors from 1977 to 2001, we find that marijuana use and attitudes are well summarized by a four-class model. Secular trends in class prevalences over this period reveal major shifts in use and attitudes. Applying a multinomial logistic model to the latent response, we investigate how class membership relates to demographic and life style factors, political beliefs and religiosity over time. Inferences about the parameters of the latent class logistic model are obtained by a combination of maximum likelihood and Bayesian techniques.