Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials.

Van Horn, M. Lee and Fagan, Abigail A. and Jaki, Thomas and Brown, Eric C. and Hawkins, J. David and Arthur, Michael W. and Abbott, Robert D. and Catalano, Richard F. (2008) Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials. Multivariate Behavioral Research, 43 (2). pp. 289-326. ISSN 0027-3171

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Abstract

There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants with certain characteristics or levels of problem behaviors. This study uses latent classes defined by clustering of individuals based on the targeted behaviors and illustrates the model by testing whether a preventive intervention aimed at reducing problem behaviors affects experimental users of illicit substances differently than problematic substance users or those individuals engaged in more serious problem behaviors. An illustrative example is used to demonstrate the identification of latent classes, specification of random effects in a multilevel mixture model, independent validation of latent classes, and the estimation of power for the proposed models to detect intervention effects. This study proposes specific steps for the estimation of multilevel mixture models and their power and suggests that this model can be applied more broadly to understand the effectiveness of interventions.

Item Type:
Journal Article
Journal or Publication Title:
Multivariate Behavioral Research
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa
Subjects:
?? EXPERIMENTAL AND COGNITIVE PSYCHOLOGYSTATISTICS AND PROBABILITYQA MATHEMATICS ??
ID Code:
81980
Deposited By:
Deposited On:
08 Oct 2016 00:06
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Sep 2023 00:05