Analyzing multiple outcomes in clinical research using multivariate multilevel models.

ABSTRACT:

Objective

Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers.

Method and results

Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix prov

SUBMITTER: Baldwin SA 

PROVIDER: S-EPMC4119868 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature