Improving efficiency of inferences in randomized clinical trials using auxiliary covariates.

Published

Journal Article

The primary goal of a randomized clinical trial is to make comparisons among two or more treatments. For example, in a two-arm trial with continuous response, the focus may be on the difference in treatment means; with more than two treatments, the comparison may be based on pairwise differences. With binary outcomes, pairwise odds ratios or log odds ratios may be used. In general, comparisons may be based on meaningful parameters in a relevant statistical model. Standard analyses for estimation and testing in this context typically are based on the data collected on response and treatment assignment only. In many trials, auxiliary baseline covariate information may also be available, and it is of interest to exploit these data to improve the efficiency of inferences. Taking a semiparametric theory perspective, we propose a broadly applicable approach to adjustment for auxiliary covariates to achieve more efficient estimators and tests for treatment parameters in the analysis of randomized clinical trials. Simulations and applications demonstrate the performance of the methods.

Full Text

Duke Authors

Cited Authors

  • Zhang, M; Tsiatis, AA; Davidian, M

Published Date

  • September 2008

Published In

Volume / Issue

  • 64 / 3

Start / End Page

  • 707 - 715

PubMed ID

  • 18190618

Pubmed Central ID

  • 18190618

Electronic International Standard Serial Number (EISSN)

  • 1541-0420

Digital Object Identifier (DOI)

  • 10.1111/j.1541-0420.2007.00976.x

Language

  • eng

Conference Location

  • United States