These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
391 related articles for article (PubMed ID: 29921006)
1. Sample size determination for GEE analyses of stepped wedge cluster randomized trials. Li F; Turner EL; Preisser JS Biometrics; 2018 Dec; 74(4):1450-1458. PubMed ID: 29921006 [TBL] [Abstract][Full Text] [Related]
2. A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials. Zhang Y; Preisser JS; Turner EL; Rathouz PJ; Toles M; Li F Stat Methods Med Res; 2023 Jan; 32(1):71-87. PubMed ID: 36253078 [TBL] [Abstract][Full Text] [Related]
3. swdpwr: A SAS macro and an R package for power calculations in stepped wedge cluster randomized trials. Chen J; Zhou X; Li F; Spiegelman D Comput Methods Programs Biomed; 2022 Jan; 213():106522. PubMed ID: 34818620 [TBL] [Abstract][Full Text] [Related]
4. Power and sample size requirements for GEE analyses of cluster randomized crossover trials. Li F; Forbes AB; Turner EL; Preisser JS Stat Med; 2019 Feb; 38(4):636-649. PubMed ID: 30298551 [TBL] [Abstract][Full Text] [Related]
5. Power considerations for generalized estimating equations analyses of four-level cluster randomized trials. Wang X; Turner EL; Preisser JS; Li F Biom J; 2022 Apr; 64(4):663-680. PubMed ID: 34897793 [TBL] [Abstract][Full Text] [Related]
6. GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials. Zhang Y; Preisser JS; Li F; Turner EL; Toles M; Rathouz PJ Comput Methods Programs Biomed; 2023 Mar; 230():107362. PubMed ID: 36709555 [TBL] [Abstract][Full Text] [Related]
7. Design and analysis considerations for cohort stepped wedge cluster randomized trials with a decay correlation structure. Li F Stat Med; 2020 Feb; 39(4):438-455. PubMed ID: 31797438 [TBL] [Abstract][Full Text] [Related]
8. Power calculation for detecting interaction effect in cross-sectional stepped-wedge cluster randomized trials: an important tool for disparity research. Yang C; Berkalieva A; Mazumdar M; Kwon D BMC Med Res Methodol; 2024 Mar; 24(1):57. PubMed ID: 38431550 [TBL] [Abstract][Full Text] [Related]
9. A readily available improvement over method of moments for intra-cluster correlation estimation in the context of cluster randomized trials and fitting a GEE-type marginal model for binary outcomes. Westgate PM Clin Trials; 2019 Feb; 16(1):41-51. PubMed ID: 30295512 [TBL] [Abstract][Full Text] [Related]
10. Generalized estimating equations in cluster randomized trials with a small number of clusters: Review of practice and simulation study. Huang S; Fiero MH; Bell ML Clin Trials; 2016 Aug; 13(4):445-9. PubMed ID: 27094487 [TBL] [Abstract][Full Text] [Related]
11. Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials. Scott JM; deCamp A; Juraska M; Fay MP; Gilbert PB Stat Methods Med Res; 2017 Apr; 26(2):583-597. PubMed ID: 25267551 [TBL] [Abstract][Full Text] [Related]
12. Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations. Wang X; Turner EL; Li F Stat Med; 2024 Jan; 43(2):358-378. PubMed ID: 38009329 [TBL] [Abstract][Full Text] [Related]
13. Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study. Barker D; D'Este C; Campbell MJ; McElduff P Trials; 2017 Mar; 18(1):119. PubMed ID: 28279222 [TBL] [Abstract][Full Text] [Related]
14. Sample size calculation in three-level cluster randomized trials using generalized estimating equation models. Liu J; Colditz GA Stat Med; 2020 Oct; 39(24):3347-3372. PubMed ID: 32720717 [TBL] [Abstract][Full Text] [Related]
15. Power calculation for analyses of cross-sectional stepped-wedge cluster randomized trials with binary outcomes via generalized estimating equations. Harrison LJ; Wang R Stat Med; 2021 Dec; 40(29):6674-6688. PubMed ID: 34558112 [TBL] [Abstract][Full Text] [Related]
16. Comparison of small-sample standard-error corrections for generalised estimating equations in stepped wedge cluster randomised trials with a binary outcome: A simulation study. Thompson JA; Hemming K; Forbes A; Fielding K; Hayes R Stat Methods Med Res; 2021 Feb; 30(2):425-439. PubMed ID: 32970526 [TBL] [Abstract][Full Text] [Related]
17. Maintaining the validity of inference in small-sample stepped wedge cluster randomized trials with binary outcomes when using generalized estimating equations. Ford WP; Westgate PM Stat Med; 2020 Sep; 39(21):2779-2792. PubMed ID: 32578264 [TBL] [Abstract][Full Text] [Related]
18. Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials. Liu J; Li F Stat Methods Med Res; 2024 Aug; 33(8):1299-1330. PubMed ID: 38813761 [TBL] [Abstract][Full Text] [Related]
19. Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes. Li P; Redden DT Stat Med; 2015 Jan; 34(2):281-96. PubMed ID: 25345738 [TBL] [Abstract][Full Text] [Related]
20. Sample size determination for stepped wedge cluster randomized trials in pragmatic settings. Wang J; Cao J; Zhang S; Ahn C Stat Methods Med Res; 2021 Jul; 30(7):1609-1623. PubMed ID: 34139916 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]