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Further Development of Flexible Parametric Models for Survival Analysis

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Lambert, Paul C., Royston, Patrick·2009·The Stata Journal: Promoting communications on statistics and Stata

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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Metadata

Authors
Lambert, P. C., & Royston, P.
Venue
The Stata Journal: Promoting communications on statistics and Stata
Published
2009-08
Volume
9
Issue
2
Pages
265-290
ISSN
  • 1536-867X (ISSN-L)
  • 1536-8734
OpenAlex
W1543389126
Cited by
814
References
0
FWCI
13.12
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Further Development of Flexible Parametric Models for Survival Analysis. https://app.cochat.ai/papers/10.1177/1536867x0900900206
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Lambert, P. C., & Royston, P. (2009). Further Development of Flexible Parametric Models for Survival Analysis. The Stata Journal: Promoting communications on statistics and Stata. https://doi.org/10.1177/1536867x0900900206

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.