Semiparametric inference for the proportional mean residual life model with right-censored length-biased data

Fangfang Bai, Jian Huang, Yong Zhou

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

We propose a semiparametric inference approach for proportional mean residual life model with right-censored length-biased data, that arise frequently in observational studies, especially in epidemiological cohort studies. A challenge in the analysis of such data is the presence of informative censoring. Another challenge is that the distribution of the observed data is different from that of the underlying model. We develop an inverse probability weighted approach to estimation based on estimating equations. We establish large sample properties and study the semiparametric efficiency and double robustness property of the proposed estimators. We also propose an improved estimator that chooses the most efficient one in the class of augmented inverse probability weighted estimators. We use simulation studies to evaluate the proposed method, and illustrate its application using a data analysis.

Original languageEnglish
Pages (from-to)1129-1158
Number of pages30
JournalStatistica Sinica
Volume26
Issue number3
DOIs
Publication statusPublished - 1 Jul 2016
Externally publishedYes

Keywords

  • Dependent censoring
  • Estimating equation
  • Length-biased data
  • Proportional mean residual model
  • Semiparametric efficiency

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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