Estimating regression parameters in an extended proportional odds model Article

Chen, YQ, Hu, N, Cheng, SC et al. (2012). Estimating regression parameters in an extended proportional odds model . JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 107(497), 318-330. 10.1080/01621459.2012.656021

cited authors

  • Chen, YQ; Hu, N; Cheng, SC; Musoke, P; Zhao, LP

authors

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 an analysis of the well-known Veterans Administration (VA) lung cancer trial. © 2012 American Statistical Association.

publication date

  • July 2, 2012

published in

Digital Object Identifier (DOI)

start page

  • 318

end page

  • 330

volume

  • 107

issue

  • 497