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Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials.

Publication ,  Journal Article
Wang, X; Turner, EL; Li, F
Published in: Biom J
March 2023

Cluster randomized trials (CRTs) frequently recruit a small number of clusters, therefore necessitating the application of small-sample corrections for valid inference. A recent systematic review indicated that CRTs reporting right-censored, time-to-event outcomes are not uncommon and that the marginal Cox proportional hazards model is one of the common approaches used for primary analysis. While small-sample corrections have been studied under marginal models with continuous, binary, and count outcomes, no prior research has been devoted to the development and evaluation of bias-corrected sandwich variance estimators when clustered time-to-event outcomes are analyzed by the marginal Cox model. To improve current practice, we propose nine bias-corrected sandwich variance estimators for the analysis of CRTs using the marginal Cox model and report on a simulation study to evaluate their small-sample properties. Our results indicate that the optimal choice of bias-corrected sandwich variance estimator for CRTs with survival outcomes can depend on the variability of cluster sizes and can also slightly differ whether it is evaluated according to relative bias or type I error rate. Finally, we illustrate the new variance estimators in a real-world CRT where the conclusion about intervention effectiveness differs depending on the use of small-sample bias corrections. The proposed sandwich variance estimators are implemented in an R package CoxBcv.

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Published In

Biom J

DOI

EISSN

1521-4036

Publication Date

March 2023

Volume

65

Issue

3

Start / End Page

e2200113

Location

Germany

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Computer Simulation
  • Cluster Analysis
  • Bias
  • 4905 Statistics
  • 0104 Statistics
 

Citation

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Wang, X., Turner, E. L., & Li, F. (2023). Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials. Biom J, 65(3), e2200113. https://doi.org/10.1002/bimj.202200113
Wang, Xueqi, Elizabeth L. Turner, and Fan Li. “Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials.Biom J 65, no. 3 (March 2023): e2200113. https://doi.org/10.1002/bimj.202200113.
Wang, Xueqi, et al. “Improving sandwich variance estimation for marginal Cox analysis of cluster randomized trials.Biom J, vol. 65, no. 3, Mar. 2023, p. e2200113. Pubmed, doi:10.1002/bimj.202200113.
Journal cover image

Published In

Biom J

DOI

EISSN

1521-4036

Publication Date

March 2023

Volume

65

Issue

3

Start / End Page

e2200113

Location

Germany

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Computer Simulation
  • Cluster Analysis
  • Bias
  • 4905 Statistics
  • 0104 Statistics