Literature DB >> 17879427

The importance and role of intracluster correlations in planning cluster trials.

John S Preisser1, Beth A Reboussin, Eun-Young Song, Mark Wolfson.   

Abstract

There is increasing recognition of the critical role of intracluster correlations of health behavior outcomes in cluster intervention trials. This study examines the estimation, reporting, and use of intracluster correlations in planning cluster trials. We use an estimating equations approach to estimate the intracluster correlations corresponding to the multiple-time-point nested cross-sectional design. Sample size formulae incorporating 2 types of intracluster correlations are examined for the purpose of planning future trials. The traditional intracluster correlation is the correlation among individuals within the same community at a specific time point. A second type is the correlation among individuals within the same community at different time points. For a "time x condition" analysis of a pretest-posttest nested cross-sectional trial design, we show that statistical power considerations based upon a posttest-only design generally are not an adequate substitute for sample size calculations that incorporate both types of intracluster correlations. Estimation, reporting, and use of intracluster correlations are illustrated for several dichotomous measures related to underage drinking collected as part of a large nonrandomized trial to enforce underage drinking laws in the United States from 1998 to 2004.

Mesh:

Year:  2007        PMID: 17879427      PMCID: PMC2567827          DOI: 10.1097/ede.0b013e3181200199

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  22 in total

Review 1.  Application of a generalized random effects regression model for cluster-correlated longitudinal data to a school-based smoking prevention trial.

Authors:  A I Sashegyi; K S Brown; P J Farrell
Journal:  Am J Epidemiol       Date:  2000-12-15       Impact factor: 4.897

2.  Analysis of dichotomous outcome data for community intervention studies.

Authors:  S L Bellamy; R Gibberd; L Hancock; P Howley; B Kennedy; N Klar; S Lipsitz; L Ryan
Journal:  Stat Methods Med Res       Date:  2000-04       Impact factor: 3.021

3.  Analysis strategies for a community trial to reduce adolescent ATOD use: a comparison of random coefficient and ANOVA/ANCOVA models.

Authors:  David M Murray; M Lee Van Horn; J David Hawkins; Michael W Arthur
Journal:  Contemp Clin Trials       Date:  2006-04       Impact factor: 2.226

4.  A comparison of two bias-corrected covariance estimators for generalized estimating equations.

Authors:  Bing Lu; John S Preisser; Bahjat F Qaqish; Chirayath Suchindran; Shrikant I Bangdiwala; Mark Wolfson
Journal:  Biometrics       Date:  2007-09       Impact factor: 2.571

5.  Intraclass correlation estimates in a school-based smoking prevention study. Outcome and mediating variables, by sex and ethnicity.

Authors:  O Siddiqui; D Hedeker; B R Flay; F B Hu
Journal:  Am J Epidemiol       Date:  1996-08-15       Impact factor: 4.897

6.  Intraclass correlation among measures related to alcohol use by school aged adolescents: estimates, correlates and applications in intervention studies.

Authors:  D M Murray; B Short
Journal:  J Drug Educ       Date:  1996

7.  Cohort versus cross-sectional design in large field trials: precision, sample size, and a unifying model.

Authors:  H A Feldman; S M McKinlay
Journal:  Stat Med       Date:  1994-01-15       Impact factor: 2.373

8.  Correlated binary regression with covariates specific to each binary observation.

Authors:  R L Prentice
Journal:  Biometrics       Date:  1988-12       Impact factor: 2.571

9.  Design of the Trial of Activity in Adolescent Girls (TAAG).

Authors:  June Stevens; David M Murray; Diane J Catellier; Peter J Hannan; Leslie A Lytle; John P Elder; Deborah R Young; Denise G Simons-Morton; Larry S Webber
Journal:  Contemp Clin Trials       Date:  2005-04       Impact factor: 2.226

10.  Intraclass correlation among measures related to alcohol use by young adults: estimates, correlates and applications in intervention studies.

Authors:  D M Murray; B Short
Journal:  J Stud Alcohol       Date:  1995-11
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  15 in total

1.  All Nations Breath of Life: A Randomized Trial of Smoking Cessation for American Indians.

Authors:  Won S Choi; Laura A Beebe; Niaman Nazir; Baljit Kaur; Michelle Hopkins; Myrietta Talawyma; Theresa I Shireman; Hung-Wen Yeh; K Allen Greiner; Christine M Daley
Journal:  Am J Prev Med       Date:  2016-07-18       Impact factor: 5.043

2.  Sample size requirements for detecting treatment effect heterogeneity in cluster randomized trials.

Authors:  Siyun Yang; Fan Li; Monique A Starks; Adrian F Hernandez; Robert J Mentz; Kingshuk R Choudhury
Journal:  Stat Med       Date:  2020-08-21       Impact factor: 2.373

3.  Power considerations for generalized estimating equations analyses of four-level cluster randomized trials.

Authors:  Xueqi Wang; Elizabeth L Turner; John S Preisser; Fan Li
Journal:  Biom J       Date:  2021-12-13       Impact factor: 1.715

4.  Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

Authors:  Beth A Reboussin; John S Preisser; Eun-Young Song; Mark Wolfson
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2012-07-01       Impact factor: 2.483

5.  Sample size considerations for GEE analyses of three-level cluster randomized trials.

Authors:  Steven Teerenstra; Bing Lu; John S Preisser; Theo van Achterberg; George F Borm
Journal:  Biometrics       Date:  2010-12       Impact factor: 2.571

6.  Power and sample size requirements for GEE analyses of cluster randomized crossover trials.

Authors:  Fan Li; Andrew B Forbes; Elizabeth L Turner; John S Preisser
Journal:  Stat Med       Date:  2018-10-08       Impact factor: 2.373

7.  Differential treatment of hypertension by primary care providers and hypertension specialists in a barber-based intervention trial to control hypertension in Black men.

Authors:  Florian Rader; Robert M Elashoff; Sara Niknezhad; Ronald G Victor
Journal:  Am J Cardiol       Date:  2013-08-23       Impact factor: 2.778

8.  Intracluster correlation coefficients and coefficients of variation for perinatal outcomes from five cluster-randomised controlled trials in low and middle-income countries: results and methodological implications.

Authors:  Christina Pagel; Audrey Prost; Sonia Lewycka; Sushmita Das; Tim Colbourn; Rajendra Mahapatra; Kishwar Azad; Anthony Costello; David Osrin
Journal:  Trials       Date:  2011-06-14       Impact factor: 2.279

9.  Marginal modeling of cluster-period means and intraclass correlations in stepped wedge designs with binary outcomes.

Authors:  Fan Li; Hengshi Yu; Paul J Rathouz; Elizabeth L Turner; John S Preisser
Journal:  Biostatistics       Date:  2022-07-18       Impact factor: 5.279

10.  Impact of unequal cluster sizes for GEE analyses of stepped wedge cluster randomized trials with binary outcomes.

Authors:  Zibo Tian; John S Preisser; Denise Esserman; Elizabeth L Turner; Paul J Rathouz; Fan Li
Journal:  Biom J       Date:  2021-10-01       Impact factor: 1.715

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