Analyzing right-censored length-biased data with additive hazards model

Mu Zhao, Cun jie Lin, Yong Zhou

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Length-biased data are often encountered in observational studies, when the survival times are left-truncated and right-censored and the truncation times follow a uniform distribution. In this article, we propose to analyze such data with the additive hazards model, which specifies that the hazard function is the sum of an arbitrary baseline hazard function and a regression function of covariates. We develop estimating equation approaches to estimate the regression parameters. The resultant estimators are shown to be consistent and asymptotically normal. Some simulation studies and a real data example are used to evaluate the finite sample properties of the proposed estimators.

Original languageEnglish
Pages (from-to)893-908
Number of pages16
JournalActa Mathematicae Applicatae Sinica
Volume33
Issue number4
DOIs
StatePublished - 1 Oct 2017
Externally publishedYes

Keywords

  • additive hazards model
  • dependent censoring
  • estimating equation
  • length-biased data

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