Document Detail


Evaluation of community-intervention trials via generalized linear mixed models.
MedLine Citation:
PMID:  15606425     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In community-intervention trials, communities, rather than individuals, are randomized to experimental arms. Generalized linear mixed models offer a flexible parametric framework for the evaluation of community-intervention trials, incorporating both systematic and random variations at the community and individual levels. We propose here a simple two-stage inference method for generalized linear mixed models, specifically tailored to the analysis of community-intervention trials. In the first stage, community-specific random effects are estimated from individual-level data, adjusting for the effects of individual-level covariates. This reduces the model approximately to a linear mixed model with the unit of analysis being community. Because the number of communities is typically small in community-intervention studies, we apply the small-sample inference method of Kenward and Roger (1997, Biometrics53, 983-997) to the linear mixed model of second stage. We show by simulation that, under typical settings of community-intervention studies, the proposed approach improves the inference on the intervention-effect parameter uniformly over both the linearized mixed-effect approach and the adaptive Gaussian quadrature approach for generalized linear mixed models. This work is motivated by a series of large randomized trials that test community interventions for promoting cancer preventive lifestyles and behaviors.
Authors:
Yutaka Yasui; Ziding Feng; Paula Diehr; Dale McLerran; Shirley A A Beresford; Charles E McCulloch
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Biometrics     Volume:  60     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  2004 Dec 
Date Detail:
Created Date:  2004-12-20     Completed Date:  2005-06-13     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1043-52     Citation Subset:  IM    
Affiliation:
Cancer Prevention Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N., P.O. Box 19024, Seattle, Washington 98109-1024, USA. yyasui@ualberta.ca
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MeSH Terms
Descriptor/Qualifier:
Biometry
Community Health Services / statistics & numerical data
Community-Institutional Relations
Cross-Sectional Studies
Data Collection
Diet
Fruit
Health Promotion / statistics & numerical data
Humans
Intervention Studies*
Linear Models*
Public Health
Randomized Controlled Trials as Topic / statistics & numerical data*
Vegetables
Washington
Grant Support
ID/Acronym/Agency:
P01-CA53996/CA/NCI NIH HHS; R01-CA84079/CA/NCI NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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