Literature DB >> 24491071

Analyzing multiple outcomes in clinical research using multivariate multilevel models.

Scott A Baldwin1, Zac E Imel2, Scott R Braithwaite1, David C Atkins3.   

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. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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Year:  2014        PMID: 24491071      PMCID: PMC4119868          DOI: 10.1037/a0035628

Source DB:  PubMed          Journal:  J Consult Clin Psychol        ISSN: 0022-006X


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