A class of transformed hazards models for recurrent gap times

Fangyuan Kang; Liuquan Sun; Xingqiu Zhao

doi:10.1016/j.csda.2014.10.005

A class of transformed hazards models for recurrent gap times

Fangyuan Kang, Liuquan Sun, Xingqiu Zhao

Research output: Journal article publication › Journal article › Academic research › peer-review

8 Citations (Scopus)

Abstract

In this article, a class of transformed hazards models is proposed for recurrent gap time data, including both the proportional and additive hazards models as special cases. An estimating equation-based inference procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, a lack-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease (CGD) is illustrated.

Original language	English
Pages (from-to)	151-167
Number of pages	17
Journal	Computational Statistics and Data Analysis
Volume	83
DOIs	https://doi.org/10.1016/j.csda.2014.10.005
Publication status	Published - 1 Jan 2015

Keywords

Estimating equations
Gap times
Model checking
Recurrent events
Transformed hazards model

ASJC Scopus subject areas

Statistics and Probability
Computational Mathematics
Computational Theory and Mathematics
Applied Mathematics

More information

10.1016/j.csda.2014.10.005

Cite this

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AB - In this article, a class of transformed hazards models is proposed for recurrent gap time data, including both the proportional and additive hazards models as special cases. An estimating equation-based inference procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, a lack-of-fit test is presented to assess the adequacy of the model. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease (CGD) is illustrated.

KW - Estimating equations

KW - Gap times

KW - Model checking

KW - Recurrent events

KW - Transformed hazards model

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JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

ER -

A class of transformed hazards models for recurrent gap times

Abstract

Keywords

ASJC Scopus subject areas

More information

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