Testing hypotheses under adaptive randomization with continuous covariates in clinical trials

Statistical Methods in Medical Research
Xiaoming LiFeifang Hu

Abstract

Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply discretizing or categorizing continuous covariates can result in loss of information. The current understanding of adaptive designs with continuous covariates lacks a theoretical foundation as the existing works are entirely based on simulations. Consequently, conventional hypothesis testing in clinical trials using continuous covariates is still not well understood. In this paper, we establish a theoretical framework for hypothesis testing on adaptive designs with continuous covariates based on linear models. For testing treatment effects and significance of covariates, we obtain the asymptotic distributions of the test statistic under null and alternative hypotheses. Simulation studies are conducted under a class of covariate-adaptive designs, including the p-value-based method, the Su's percentile method, the empirical cumulative-distribution method, the Kullback-Leibler divergence method, and the kernel-density met...Continue Reading

References

Jun 1, 1987·Computers and Biomedical Research, an International Journal·F K Hoehler
Jun 1, 1985·Controlled Clinical Trials·N J Birkett
May 1, 1974·Clinical Pharmacology and Therapeutics·D R Taves
Feb 15, 2003·Statistics in Medicine·Christopher J Weir, Kennedy R Lees
Dec 14, 2004·Controlled Clinical Trials·Atsushi HaginoHiroaki Nakazato
Dec 17, 2009·Contemporary Clinical Trials·Bjarne Stigsby, Donald R Taves
Mar 9, 2011·Contemporary Clinical Trials·Zheng Su
Dec 29, 2012·Contemporary Clinical Trials·Zhenjun Ma, Feifang Hu

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Citations

Mar 19, 2021·Statistics in Medicine·Xin LiFeifang Hu
Aug 10, 2021·Pharmaceutical Statistics·Wanying ZhaoFeifang Hu

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