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

Research output: Contribution to journalJournal articlepeer-review

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Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials. / Van Horn, M. Lee; Fagan, Abigail A.; Jaki, Thomas; Brown, Eric C.; Hawkins, J. David; Arthur, Michael W.; Abbott, Robert D.; Catalano, Richard F.

In: Multivariate Behavioral Research, Vol. 43, No. 2, 04.2008, p. 289-326.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Van Horn, ML, Fagan, AA, Jaki, T, Brown, EC, Hawkins, JD, Arthur, MW, Abbott, RD & Catalano, RF 2008, 'Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials.', Multivariate Behavioral Research, vol. 43, no. 2, pp. 289-326. https://doi.org/10.1080/00273170802034893

APA

Van Horn, M. L., Fagan, A. A., Jaki, T., Brown, E. C., Hawkins, J. D., Arthur, M. W., Abbott, R. D., & Catalano, R. F. (2008). Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials. Multivariate Behavioral Research, 43(2), 289-326. https://doi.org/10.1080/00273170802034893

Vancouver

Van Horn ML, Fagan AA, Jaki T, Brown EC, Hawkins JD, Arthur MW et al. Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials. Multivariate Behavioral Research. 2008 Apr;43(2):289-326. https://doi.org/10.1080/00273170802034893

Author

Van Horn, M. Lee ; Fagan, Abigail A. ; Jaki, Thomas ; Brown, Eric C. ; Hawkins, J. David ; Arthur, Michael W. ; Abbott, Robert D. ; Catalano, Richard F. / Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials. In: Multivariate Behavioral Research. 2008 ; Vol. 43, No. 2. pp. 289-326.

Bibtex

@article{dd1bfbfd4d264d2e8401caff7b1a987e,
title = "Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials.",
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.",
author = "{Van Horn}, {M. Lee} and Fagan, {Abigail A.} and Thomas Jaki and Brown, {Eric C.} and Hawkins, {J. David} and Arthur, {Michael W.} and Abbott, {Robert D.} and Catalano, {Richard F.}",
year = "2008",
month = apr,
doi = "10.1080/00273170802034893",
language = "English",
volume = "43",
pages = "289--326",
journal = "Multivariate Behavioral Research",
issn = "0027-3171",
publisher = "Psychology Press Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials.

AU - Van Horn, M. Lee

AU - Fagan, Abigail A.

AU - Jaki, Thomas

AU - Brown, Eric C.

AU - Hawkins, J. David

AU - Arthur, Michael W.

AU - Abbott, Robert D.

AU - Catalano, Richard F.

PY - 2008/4

Y1 - 2008/4

N2 - 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.

AB - 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.

U2 - 10.1080/00273170802034893

DO - 10.1080/00273170802034893

M3 - Journal article

VL - 43

SP - 289

EP - 326

JO - Multivariate Behavioral Research

JF - Multivariate Behavioral Research

SN - 0027-3171

IS - 2

ER -