HAZARD REGRESSION

• 成果类型: Article
• 署名作者: KOOPERBERG, C; STONE, CJ; TRUONG, YK
• 署名单位: University of California System; University of California Berkeley; University of North Carolina; University of North Carolina Chapel Hill
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2291132
• 发表日期: 1995
• 页码: 78-94
• 关键词: censored survival-data; PENALIZED LIKELIHOOD; splines; estimators; density; models

摘要

Linear splines and their tenser products are used to estimate the conditional log-hazard function based on possibly censored, positive response data and one or more covariates. An automatic procedure involving the maximum likelihood method, stepwise addition, stepwise deletion, and the Bayes Information Criterion is used to select the final model. The possible models contain proportional hazards models as a subclass, which makes it possible to diagnose departures from proportionality. Cubic splines and two additional log terms are incorporated into a similar model for the unconditional log-hazard function to allow for greater flexibility in the extreme tails. A user interface based on S is described.