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The Stata Journal
Volume 9 Number 2: pp. 265-290

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Further development of flexible parametric models for survival analysis

Paul C. Lambert
Centre for Biostatistics and Genetic Epidemiology
Department of Health Sciences
University of Leicester, UK
Patrick Royston
Clinical Trials Unit
Medical Research Council
London, UK
Abstract.  Royston and Parmar (2002, Statistics in Medicine 21: 2175–2197) developed a class of flexible parametric survival models that were programmed in Stata with the stpm command (Royston, 2001, Stata Journal 1: 1–28). In this article, we introduce a new command, stpm2, that extends the methodology. New features for stpm2 include improvement in the way time-dependent covariates are modeled, with these effects far less likely to be over parameterized; the ability to incorporate expected mortality and thus fit relative survival models; and a superior predict command that enables simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences. The ideas are illustrated through a study of breast cancer survival and incidence of hip fracture in prostate cancer patients.
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