协变量
参数统计
生存分析
参数化模型
危害
统计
比例危险模型
相对存活率
计算机科学
危险系数
医学
计量经济学
数学
癌症
癌症登记处
内科学
生物
置信区间
生态学
作者
Paul C. Lambert,Patrick Royston
出处
期刊:Stata Journal
[SAGE Publishing]
日期:2009-08-01
卷期号:9 (2): 265-290
被引量:823
标识
DOI:10.1177/1536867x0900900206
摘要
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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