A semi-parametric accelerated failure time cure model

Chin-Shang Li, Jeremy M G Taylor

Research output: Contribution to journalArticle

52 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)3235-3247
Number of pages13
JournalStatistics in Medicine
Volume21
Issue number21
DOIs
StatePublished - Nov 15 2002
Externally publishedYes

Fingerprint

Cure Model
Accelerated Failure Time Model
Latency
Incidence
Tonsillar Neoplasms
Logistic Models
Medical Errors
Radiation Therapy
Failure Time Data
Logistic Regression Model
Semiparametric Model
Radiotherapy
EM Algorithm
Covariates
Regression Model
Cancer
Denote
Experience

Keywords

  • Accelerated failure time model
  • Cure model
  • EM algorithm
  • Incidence
  • Latency

ASJC Scopus subject areas

  • Epidemiology

Cite this

A semi-parametric accelerated failure time cure model. / Li, Chin-Shang; Taylor, Jeremy M G.

In: Statistics in Medicine, Vol. 21, No. 21, 15.11.2002, p. 3235-3247.

Research output: Contribution to journalArticle

Li, Chin-Shang ; Taylor, Jeremy M G. / A semi-parametric accelerated failure time cure model. In: Statistics in Medicine. 2002 ; Vol. 21, No. 21. pp. 3235-3247.
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