Literature DB >> 7973205

Estimation and sample size considerations for clustered binary responses.

E W Lee1, N Dubin.   

Abstract

Although there is much literature on sample size determination for clinical trials or experiments with independent responses, there is a lack of methodology to obtain sample sizes for dependent outcomes. This paper presents a simple way to calculate sample size for estimating treatment effects and diagnostic accuracy in the case of correlated binary outcomes. The proposed weighted procedure also has use in estimation, whose advantages we demonstrate through simulation. Recommendations are made for practical application.

Mesh:

Year:  1994        PMID: 7973205     DOI: 10.1002/sim.4780131206

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


  11 in total

Review 1.  Sample size estimation in research with dependent measures and dichotomous outcomes.

Authors:  Kevin L Delucchi
Journal:  Am J Public Health       Date:  2004-03       Impact factor: 9.308

2.  Nonparametric Sample Size Estimation for Sensitivity and Specificity with Multiple Observations per Subject.

Authors:  Fan Hu; William R Schucany; Chul Ahn
Journal:  Drug Inf J       Date:  2010

3.  Sample Size Calculation for Clustered Binary Data with Sign Tests Using Different Weighting Schemes.

Authors:  Chul Ahn; Fan Hu; William R Schucany
Journal:  Stat Biopharm Res       Date:  2011-02-01       Impact factor: 1.452

4.  Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes.

Authors:  Peng Li; David T Redden
Journal:  Stat Med       Date:  2014-10-24       Impact factor: 2.373

5.  Optimal design of longitudinal data analysis using generalized estimating equation models.

Authors:  Jingxia Liu; Graham A Colditz
Journal:  Biom J       Date:  2016-11-23       Impact factor: 2.207

6.  Clinical determinants for successful circulating tumor DNA analysis in prostate cancer.

Authors:  Michael T Schweizer; Roman Gulati; Mallory Beightol; Eric Q Konnick; Heather H Cheng; Nola Klemfuss; Navonil De Sarkar; Evan Y Yu; R Bruce Montgomery; Peter S Nelson; Colin C Pritchard
Journal:  Prostate       Date:  2019-03-13       Impact factor: 4.104

7.  Collaborative quality improvement to promote evidence based surfactant for preterm infants: a cluster randomised trial.

Authors:  Jeffrey D Horbar; Joseph H Carpenter; Jeffrey Buzas; Roger F Soll; Gautham Suresh; Michael B Bracken; Laura C Leviton; Paul E Plsek; John C Sinclair
Journal:  BMJ       Date:  2004-10-30

8.  A comparison of three scores to screen for delirium on the surgical ward.

Authors:  Finn M Radtke; Martin Franck; Sabine Schust; Lina Boehme; Andreas Pascher; Hermann J Bail; Matthes Seeling; Alawi Luetz; Klaus-D Wernecke; Andreas Heinz; Claudia D Spies
Journal:  World J Surg       Date:  2010-03       Impact factor: 3.352

9.  Comparing Multiple Sensitivities and Specificities with Different Diagnostic Criteria: Applications to Sexual Abuse and Sexual Health Research.

Authors:  Q Yu; W Tang; Y Ma; S A Gamble; X M Tu
Journal:  Comput Stat Data Anal       Date:  2008-09       Impact factor: 1.681

10.  Comparison of population-averaged and cluster-specific models for the analysis of cluster randomized trials with missing binary outcomes: a simulation study.

Authors:  Jinhui Ma; Parminder Raina; Joseph Beyene; Lehana Thabane
Journal:  BMC Med Res Methodol       Date:  2013-01-23       Impact factor: 4.615

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