Literature DB >> 10937329

Statistical power and optimal design for multisite randomized trials.

S W Raudenbush1, X Liu.   

Abstract

The multisite trial, widely used in mental health research and education, enables experimenters to assess the average impact of a treatment across sites, the variance of treatment impact across sites, and the moderating effect of site characteristics on treatment efficacy. Key design decisions include the sample size per site and the number of sites. To consider power implications, this article proposes a standardized hierarchical linear model and uses rules of thumb similar to those proposed by J. Cohen (1988) for small, medium, and large effect sizes and for small, medium, and large treatment-by-site variance. Optimal allocation of resources within and between sites as a function of variance components and costs at each level are also considered. The approach generalizes to quasiexperiments with a similar structure. These ideas are illustrated with newly developed software.

Mesh:

Year:  2000        PMID: 10937329     DOI: 10.1037/1082-989x.5.2.199

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  86 in total

1.  The study designed by a committee: design of the Multisite Violence Prevention Project.

Authors:  David B Henry; Albert D Farrell
Journal:  Am J Prev Med       Date:  2004-01       Impact factor: 5.043

2.  Brief strategic family therapy versus treatment as usual: results of a multisite randomized trial for substance using adolescents.

Authors:  Michael S Robbins; Daniel J Feaster; Viviana E Horigian; Michael Rohrbaugh; Varda Shoham; Ken Bachrach; Michael Miller; Kathleen A Burlew; Candy Hodgkins; Ibis Carrion; Nancy Vandermark; Eric Schindler; Robert Werstlein; José Szapocznik
Journal:  J Consult Clin Psychol       Date:  2011-10-03

3.  Multisite effectiveness trials of treatments for substance abuse and co-occurring problems: have we chosen the best designs?

Authors:  Edward V Nunes; Samuel Ball; Robert Booth; Gregory Brigham; Donald A Calsyn; Kathleen Carroll; Daniel J Feaster; Denise Hien; Robert L Hubbard; Walter Ling; Nancy M Petry; John Rotrosen; Jeffrey Selzer; Maxine Stitzer; Susan Tross; Paul Wakim; Theresa Winhusen; George Woody
Journal:  J Subst Abuse Treat       Date:  2010-06

Review 4.  Multilevel factorial experiments for developing behavioral interventions: power, sample size, and resource considerations.

Authors:  John J Dziak; Inbal Nahum-Shani; Linda M Collins
Journal:  Psychol Methods       Date:  2012-02-06

5.  The Effectiveness and Cost of Clinical Supervision for Motivational Interviewing: A Randomized Controlled Trial.

Authors:  Steve Martino; Manuel Paris; Luis Añez; Charla Nich; Monica Canning-Ball; Karen Hunkele; Todd A Olmstead; Kathleen M Carroll
Journal:  J Subst Abuse Treat       Date:  2016-05-08

6.  Statistical issues in multisite effectiveness trials: the case of brief strategic family therapy for adolescent drug abuse treatment.

Authors:  Daniel J Feaster; Michael S Robbins; Viviana Horigian; José Szapocznik
Journal:  Clin Trials       Date:  2004       Impact factor: 2.486

7.  Dismantling motivational interviewing and feedback for college drinkers: a randomized clinical trial.

Authors:  Scott T Walters; Amanda M Vader; T Robert Harris; Craig A Field; Ernest N Jouriles
Journal:  J Consult Clin Psychol       Date:  2009-02

Review 8.  Optimal Design and Purposeful Sampling: Complementary Methodologies for Implementation Research.

Authors:  Naihua Duan; Dulal K Bhaumik; Lawrence A Palinkas; Kimberly Hoagwood
Journal:  Adm Policy Ment Health       Date:  2015-09

9.  Organizational implementation of evidence-based substance abuse treatment in racial and ethnic minority communities.

Authors:  Erick G Guerrero; Amy He; Ahraemi Kim; Gregory A Aarons
Journal:  Adm Policy Ment Health       Date:  2014-11

10.  Sample size requirements to detect an intervention by time interaction in longitudinal cluster randomized clinical trials with random slopes.

Authors:  Moonseong Heo; Xiaonan Xue; Mimi Y Kim
Journal:  Comput Stat Data Anal       Date:  2013-04-01       Impact factor: 1.681

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