JOURNAL ARTICLE

A semi‐parametric accelerated failure time cure model

Chin‐Shang LiJeremy M. G. Taylor

Year: 2002 Journal:   Statistics in Medicine Vol: 21 (21)Pages: 3235-3247   Publisher: Wiley

Abstract

Abstract A cure model is a useful approach for analysing failure time data in which some subjects could eventually experience, and others never experience, the event of interest. A cure model has two components: incidence which indicates whether the event could eventually occur and latency which denotes when the event will occur given the subject is susceptible to the event. In this paper, we propose a semi‐parametric cure model in which covariates can affect both the incidence and the latency. A logistic regression model is proposed for the incidence, and the latency is determined by an accelerated failure time regression model with unspecified error distribution. An EM algorithm is developed to fit the model. The procedure is applied to a data set of tonsil cancer patients treated with radiation therapy. Copyright © 2002 John Wiley & Sons, Ltd.

Keywords:
Accelerated failure time model Logistic regression Covariate Computer science Parametric statistics Statistics Proportional hazards model Latency (audio) Incidence (geometry) Event data Event (particle physics) Econometrics Mathematics

Metrics

121
Cited By
2.05
FWCI (Field Weighted Citation Impact)
19
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Statistical Methods and Inference
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Distribution Estimation and Applications
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Methods in Clinical Trials
Physical Sciences →  Mathematics →  Statistics and Probability

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