Analysis of multivariate longitudinal substance use outcomes using multivariate mixed cumulative logit model.

ABSTRACT:

Background

Longitudinal assessments of usage are often conducted for multiple substances (e.g., cigarettes, alcohol and marijuana) and research interests are often focused on the inter-substance association. We propose a multivariate longitudinal modeling approach for jointly analyzing the ordinal multivariate substance use data.

Methods

We describe how the binary random slope logistic regression model can be extended to the multi-category ordinal outcomes. We also describe how the proportional odds assumption can be relaxed by allowing differential covariate effects on different cumulative logits for multiple outcomes. Data are analyzed from a P01 study that evaluates the usage levels of cigarettes, alcohol and marijuana repeatedly across 8 measurement waves during 7 consec

SUBMITTER: Lin X 

PROVIDER: S-EPMC8571881 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature