www.uhasselt.be
DSpace

Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24157

Title: Covariate Adjustment for Logistic Regression Analysis of Binary Clinical Trial Data
Authors: Jiang, Honghua
Kulkarni, Pandurang M.
Mallinckrodt, Craig H.
Shurzinske, Linda
Molenberghs, Geert
Lipkovich, Ilya
Issue Date: 2017
Publisher: AMER STATISTICAL ASSOC
Citation: STATISTICS IN BIOPHARMACEUTICAL RESEARCH, 9(1), p. 126-134
Abstract: In linear regression models, covariate-adjusted analysis is not expected to change the estimates of the treatment effect in the clinical trials with randomized treatment assignment but rather to increase the precision of the estimates. However, the covariate-adjusted treatment effect estimates are generally not equivalent to the unadjusted estimates in logistic regression analysis for binary clinical trial data. In this article, we report the results of a simulation study conducted to quantify the magnitude of difference between the estimands underlying the two estimators in logistic regression. The simulation results demonstrated that both unadjusted and adjusted analyses preserved Type I error at the nominal level. The covariate-adjusted analysis produced unbiased, larger treatment effect estimates, larger standard error, and increased power comparedwith the unadjusted analysiswhen the sample sizewas large. The unadjusted analysis resulted in biased estimates of treatment effect. Analysis results for five phase 3 diabetes trials of the same compound were consistent with the simulation findings. Therefore, covariate-adjusted analysis is recommended for evaluating binary outcomes in clinical data.
Notes: [Jiang, Honghua; Kulkarni, Pandurang M.; Mallinckrodt, Craig H.; Shurzinske, Linda] Eli Lilly & Co, Lilly Res Labs, Indianapolis, IN 46285 USA. [Molenberghs, Geert] Hasselt Univ, I BioStat, Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, I BioStat, Leuven, Belgium. [Lipkovich, Ilya] Quintiles, Morrisville, NC USA.
URI: http://hdl.handle.net/1942/24157
DOI: 10.1080/19466315.2016.1234973
ISI #: 000397258400013
ISSN: 1946-6315
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Peer-reviewed author version671.31 kBAdobe PDF
Published version729.85 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.