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J Am Stat Assoc. 2012 Mar 1;107(497):318-330. Epub 2012 Jan 31.

Estimating Regression Parameters in an Extended Proportional Odds Model.

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  • 1Full Member, Vaccine and Infectious Disease and, Fred Hutchinson Cancer Research Center, Seattle, WA 98109.

Abstract

The proportional odds model may serve as a useful alternative to the Cox proportional hazards model to study association between covariates and their survival functions in medical studies. In this article, we study an extended proportional odds model that incorporates the so-called "external" time-varying covariates. In the extended model, regression parameters have a direct interpretation of comparing survival functions, without specifying the baseline survival odds function. Semiparametric and maximum likelihood estimation procedures are proposed to estimate the extended model. Our methods are demonstrated by Monte-Carlo simulations, and applied to a landmark randomized clinical trial of a short course Nevirapine (NVP) for mother-to-child transmission (MTCT) of human immunodeficiency virus type-1 (HIV-1). Additional application includes analysis of the well-known Veterans Administration (VA) Lung Cancer Trial.

PMID:
22904583
[PubMed]
PMCID:
PMC3420072
Free PMC Article
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