Literature DB >> 29921006

Sample size determination for GEE analyses of stepped wedge cluster randomized trials.

Fan Li1, Elizabeth L Turner1,2, John S Preisser3.   

Abstract

In stepped wedge cluster randomized trials, intact clusters of individuals switch from control to intervention from a randomly assigned period onwards. Such trials are becoming increasingly popular in health services research. When a closed cohort is recruited from each cluster for longitudinal follow-up, proper sample size calculation should account for three distinct types of intraclass correlations: the within-period, the inter-period, and the within-individual correlations. Setting the latter two correlation parameters to be equal accommodates cross-sectional designs. We propose sample size procedures for continuous and binary responses within the framework of generalized estimating equations that employ a block exchangeable within-cluster correlation structure defined from the distinct correlation types. For continuous responses, we show that the intraclass correlations affect power only through two eigenvalues of the correlation matrix. We demonstrate that analytical power agrees well with simulated power for as few as eight clusters, when data are analyzed using bias-corrected estimating equations for the correlation parameters concurrently with a bias-corrected sandwich variance estimator.
© 2018, The International Biometric Society.

Entities:  

Keywords:  Finite sample correction; Generalized estimating equations (GEE); Group randomized trials; Matrix-adjusted estimating equations (MAEE); Power; Sandwich estimator

Mesh:

Year:  2018        PMID: 29921006      PMCID: PMC6461045          DOI: 10.1111/biom.12918

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  24 in total

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Authors:  Fan Li; Michael O Harhay
Journal:  Int J Epidemiol       Date:  2020-06-01       Impact factor: 7.196

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.  Optimal designs in three-level cluster randomized trials with a binary outcome.

Authors:  Jingxia Liu; Lei Liu; Graham A Colditz
Journal:  Stat Med       Date:  2019-06-04       Impact factor: 2.373

4.  Statistical Considerations for Embedded Pragmatic Clinical Trials in People Living with Dementia.

Authors:  Heather G Allore; Keith S Goldfeld; Roee Gutman; Fan Li; Joan K Monin; Monica Taljaard; Thomas G Travison
Journal:  J Am Geriatr Soc       Date:  2020-07       Impact factor: 5.562

5.  Constrained randomization and statistical inference for multi-arm parallel cluster randomized controlled trials.

Authors:  Yunji Zhou; Elizabeth L Turner; Ryan A Simmons; Fan Li
Journal:  Stat Med       Date:  2022-02-10       Impact factor: 2.373

6.  Sample size calculation in hierarchical 2 × 2 factorial trials with unequal cluster sizes.

Authors:  Zizhong Tian; Denise Esserman; Guangyu Tong; Ondrej Blaha; James Dziura; Peter Peduzzi; Fan Li
Journal:  Stat Med       Date:  2022-01-02       Impact factor: 2.373

7.  Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure.

Authors:  Fan Li
Journal:  Stat Med       Date:  2019-12-04       Impact factor: 2.373

8.  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

9.  Power calculation for cross-sectional stepped wedge cluster randomized trials with variable cluster sizes.

Authors:  Linda J Harrison; Tom Chen; Rui Wang
Journal:  Biometrics       Date:  2019-11-14       Impact factor: 2.571

10.  xtgeebcv: A command for bias-corrected sandwich variance estimation for GEE analyses of cluster randomized trials.

Authors:  John A Gallis; Fan Li; Elizabeth L Turner
Journal:  Stata J       Date:  2020-06-19       Impact factor: 2.637

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