Model-Robust and Efficient Covariate Adjustment for Cluster-Randomized Experiments

Author:

Wang Bingkai1,Park Chan1,Small Dylan S.1,Li Fan2ORCID

Affiliation:

1. The Statistics and Data Science Department of the Wharton School, University of Pennsylvania, Philadelphia, PA

2. Department of Biostatistics and Center for Methods in Implementation and Prevention Science, Yale School of Public Health, New Haven, CT

Funder

Patient-Centered Outcomes Research Institute

National Institute of Allergy and Infectious Diseases

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference42 articles.

1. Two-Stage TMLE to reduce bias and improve efficiency in cluster randomized trials

2. A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure

3. Benitez A. Petersen M. L. van der Laan M. J. Santos N. Butrick E. Walker D. Ghosh R. Otieno P. Waiswa P. and Balzer L. B. (2021) “Comparative Methods for the Analysis of Cluster Randomized Trials ” arXiv preprint arXiv:2110.09633.

4. Bray, J. W., Kelly, E. L., Hammer, L. B., Almeida, D. M., Dearing, J. W., King, R. B., and Buxton, O. M. (2013), An Integrative, Multilevel, and Transdisciplinary Research Approach to Challenges of Work, Family, and Health, Methods Report, pp. 1–38, Research Triangle Park, NC: RTI Press.

5. Approximate Inference in Generalized Linear Mixed Models

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Demystifying estimands in cluster-randomised trials;Statistical Methods in Medical Research;2024-05-23

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