Latent class analysis (LCA) has proven to be a useful tool for identifying qualitatively different population subgroups who may be at varying levels of risk for negative outcomes. Recent methodological work has improved techniques for linking latent class membership to distal outcomes; however, these techniques do not adjust for potential confounding variables that may provide alternative explanations for observed relations. Inverse propensity score weighting provides a way to account for many confounders simultaneously, thereby strengthening causal inference of the effects of predictors on outcomes. Although propensity score weighting has been adapted to LCA with covariates, there has been limited work adapting it to LCA with distal outcomes. The current study proposes a step-by-step approach for using inverse propensity score weighting together with the “Bolck, Croon, and Hagenaars” approach to LCA with distal outcomes (i.e., the BCH approach), in order to estimate the causal effects of reasons for alcohol use latent class membership during the year after high school (at age 19) on later problem alcohol use (at age 35) with data from the longitudinal sample in the Monitoring the Future study. A supplementary appendix provides evidence for the accuracy of the proposed approach via a small-scale simulation study, as well as sample programming code to conduct the step-by-step approach.
Bibliographical noteFunding Information:
Funding This research was conducted at The Pennsylvania State University and The University of Michigan, and was supported by a seed grant from the National Center for Responsible Gaming (NCRG) and awards P50-DA039838, P50-DA010075, and R01-DA037902 from the National Institute on Drug Abuse (NIDA); data collection was supported by awards R01-DA001411 and R01-DA016575 from NIDA.
© 2018, Society for Prevention Research.
- Alcohol use
- Causal inference
- Latent class analysis
- Propensity scores
- Reasons for drinking