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
[email protected]
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Patrick Royston
Clinical Trials Unit
Medical Research Council
London, UK
[email protected]
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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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Paul C. Lambert, Patrick Royston
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stpm2, survival analysis, relative survival, time-dependent effects
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