Literature DB >> 2218196

Assessing the gain in efficiency due to matching in a community intervention study.

L S Freedman1, S B Green, D P Byar.   

Abstract

COMMIT (Community Intervention Trial for Smoking Cessation) is a randomized study employing a matched pairs design. Pairs of communities were selected on the basis of their geographical proximity and were chosen to be matched on variables strongly expected to relate to the outcome variable, the smoking quit rate. However, quantitative information was not available to evaluate the efficiency gain from matching. We have used baseline smoking quit rates in the communities as a surrogate for the outcome measure to evaluate the gain in efficiency from the matching. Our method takes account of the possible imperfection of the surrogate as a representative of the true outcome. The method estimates an efficiency gain of at least 50 per cent using the matched design. We also evaluate the further gains in efficiency which would be made by using the baseline quit rate to balance the randomization.

Mesh:

Year:  1990        PMID: 2218196     DOI: 10.1002/sim.4780090810

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  8 in total

Review 1.  Accounting for cluster randomization: a review of primary prevention trials, 1990 through 1993.

Authors:  J M Simpson; N Klar; A Donnor
Journal:  Am J Public Health       Date:  1995-10       Impact factor: 9.308

2.  Community Intervention Trial for Smoking Cessation (COMMIT): I. cohort results from a four-year community intervention.

Authors: 
Journal:  Am J Public Health       Date:  1995-02       Impact factor: 9.308

3.  Community intervention trial for smoking cessation (COMMIT): II. Changes in adult cigarette smoking prevalence.

Authors: 
Journal:  Am J Public Health       Date:  1995-02       Impact factor: 9.308

4.  ADAPTIVE MATCHING IN RANDOMIZED TRIALS AND OBSERVATIONAL STUDIES.

Authors:  Mark J van der Laan; Laura B Balzer; Maya L Petersen
Journal:  J Stat Res       Date:  2012-12-01

5.  The impact of HIV and high-risk behaviours on the wives of married men who have sex with men and injection drug users: implications for HIV prevention.

Authors:  Sunil S Solomon; Shruti H Mehta; Amanda Latimore; Aylur K Srikrishnan; David D Celentano
Journal:  J Int AIDS Soc       Date:  2010-06-23       Impact factor: 5.396

6.  Methods for sample size determination in cluster randomized trials.

Authors:  Clare Rutterford; Andrew Copas; Sandra Eldridge
Journal:  Int J Epidemiol       Date:  2015-07-13       Impact factor: 7.196

7.  Promoting state health department evidence-based cancer and chronic disease prevention: a multi-phase dissemination study with a cluster randomized trial component.

Authors:  Peg Allen; Sonia Sequeira; Rebekah R Jacob; Adriano Akira Ferreira Hino; Katherine A Stamatakis; Jenine K Harris; Lindsay Elliott; Jon F Kerner; Ellen Jones; Maureen Dobbins; Elizabeth A Baker; Ross C Brownson
Journal:  Implement Sci       Date:  2013-12-13       Impact factor: 7.327

8.  A multilevel approach for promoting physical activity in rural communities: a cluster randomized controlled trial.

Authors:  Alan M Beck; Amy A Eyler; J Aaron Hipp; Abby C King; Rachel G Tabak; Yan Yan; Rodrigo S Reis; Dixie D Duncan; Amanda S Gilbert; Natalicio H Serrano; Ross C Brownson
Journal:  BMC Public Health       Date:  2019-01-30       Impact factor: 3.295

  8 in total

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