Open Access
Translator Disclaimer
September 2013 Likelihood reweighting methods to reduce potential bias in noninferiority trials which rely on historical data to make inference
Lei Nie, Zhiwei Zhang, Daniel Rubin, Jianxiong Chu
Ann. Appl. Stat. 7(3): 1796-1813 (September 2013). DOI: 10.1214/13-AOAS655

Abstract

It is generally believed that bias is minimized in well-controlled randomized clinical trials. However, bias can arise in active controlled noninferiority trials because the inference relies on a previously estimated effect size obtained from a historical trial that may have been conducted for a different population. By implementing a likelihood reweighting method through propensity scoring, a study designed to estimate a treatment effect in one trial population can be used to estimate the treatment effect size in a different target population. We illustrate this method in active controlled noninferiority trials, although it can also be used in other types of studies, such as historically controlled trials, meta-analyses, and comparative effectiveness analyses.

Citation

Download Citation

Lei Nie. Zhiwei Zhang. Daniel Rubin. Jianxiong Chu. "Likelihood reweighting methods to reduce potential bias in noninferiority trials which rely on historical data to make inference." Ann. Appl. Stat. 7 (3) 1796 - 1813, September 2013. https://doi.org/10.1214/13-AOAS655

Information

Published: September 2013
First available in Project Euclid: 3 October 2013

zbMATH: 06237198
MathSciNet: MR3127969
Digital Object Identifier: 10.1214/13-AOAS655

Keywords: bias , generalized linear model , inverse probability weighting , noninferiority , propensity score

Rights: Copyright © 2013 Institute of Mathematical Statistics

JOURNAL ARTICLE
18 PAGES


SHARE
Vol.7 • No. 3 • September 2013
Back to Top