Keywords

intervention data; multilevel; multivariate

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 provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions—Multivariate multilevel models are flexible, powerful models that can enhance clinical research.

Document Type

Peer-Reviewed Article

Publication Date

2014-10

Language

English

College

Family, Home, and Social Sciences

Department

Psychology

Included in

Psychology Commons

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