Advanced search
Publication Cover
Statistical Theory and Related Fields Volume 7, 2023 - Issue 2
Submit an article Journal homepage
1,908
Views
0
CrossRef citations to date
0
Altmetric
Articles

Robust variance estimation for covariate-adjusted unconditional treatment effect in randomized clinical trials with binary outcomes

Ting Yea Department of Biostatistics, University of Washington, Seattle, WA, USACorrespondence[email protected]
View further author information
,
Marlena Bannicka Department of Biostatistics, University of Washington, Seattle, WA, USAView further author information
,
Yanyao Yib Global Statistical Sciences, Eli Lilly and Company, Indianapolis, IN, USAView further author information
&
Jun Shaoc School of Statistics, East China Normal University, Shanghai, People's Republic of China;d Department of Statistics, University of Wisconsin, Madison, WI, USAView further author information
Pages 159-163 | Received 20 Feb 2023, Accepted 18 Apr 2023, Published online: 28 Apr 2023

References

  • FDA (2021). Adjusting for covariates in randomized clinical trials for drugs and biological products. Draft Guidance for Industry. Center for Drug Evaluation and Research and Center for Biologics Evaluation and Research, Food and Drug Administration (FDA), U.S. Department of Health and Human Services, May 2021.
  • ICH E9 (R1) (2019). Addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials. International Council for Harmonisation (ICH).
  • Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., & Newey, W. (2017). Double/debiased/neyman machine learning of treatment effects. American Economic Review, 107(5), 261–265. https://doi.org/10.1257/aer.p20171038
  • Freedman, D. A. (2008). Randomization does not justify logistic regression. Statistical Science, 23(2), 237–249. https://doi.org/10.1214/08-STS262
  • Ge, M., Durham, L. K., Meyer, R. D., Xie, W., & Thomas, N. (2011). Covariate-adjusted difference in proportions from clinical trials using logistic regression and weighted risk differences. Drug Information Journal: DIJ/Drug Information Association, 45(4), 481–493. https://doi.org/10.1177/009286151104500409
  • Haldane, S. (1956). The estimation and significant of the logarithm of a ratio of frequencies. Annals of Human Genetics, 20(4), 309–311. https://doi.org/10.1111/ahg.1956.20.issue-4
  • Kennedy, E. H. (2016). Semiparametric theory and empirical processes in causal inference. In Statistical causal inferences and their applications in public health research (pp. 141–167).
  • Lin, W. (2013). Agnostic notes on regression adjustments to experimental data: Reexamining freedman's critique. Annals of Applied Statistics, 7(1), 295–318. https://doi.org/10.1214/12-AOAS583
  • Moore, K. L., & van der Laan, M. J. (2009). Covariate adjustment in randomized trials with binary outcomes: Targeted maximum likelihood estimation. Statistics in Medicine, 28(1), 39–64. https://doi.org/10.1002/sim.v28:1
  • Tsiatis, A. A., Davidian, M., Zhang, M., & Lu, X. (2008). Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: A principled yet flexible approach. Statistics in Medicine, 27(23), 4658–4677. https://doi.org/10.1002/sim.v27:23
  • Woolf, B. (1955). On estimating the relation between blood group and disease. Annals of Human Genetics, 19(4), 251–253. https://doi.org/10.1111/ahg.1955.19.issue-4
  • Yang, L., & Tsiatis, A. A. (2001). Efficiency study of estimators for a treatment effect in a pretest–posttest trial. The American Statistician, 55(4), 314–321. https://doi.org/10.1198/000313001753272466
  • Ye, T., Shao, J., Yi, Y., & Zhao, Q. (2023). Toward better practice of covariate adjustment in analyzing randomized clinical trials. Journal of the American Statistical Association, 117, in press. https://doi.org/10.1080/01621459.2022.2049278
  • Ye, T., Yi, Y., & Shao, J. (2022). Inference on average treatment effect under minimization and other covariate-adaptive randomization methods. Biometrika, 109(1), 33–47. https://doi.org/10.1093/biomet/asab015

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.