Doubly robust semiparametric estimation for the missing censoring indicator model

Sundarraman Subramanian, Dipankar Bandyopadhyay

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We present a semiparametric analysis of an augmented inverse probability of non-missingness weighted (AIPW) estimator of a survival function for the missing censoring indicator model. Although the estimator is asymptotically less efficient than a Dikta semiparametric estimator, its advantage is the insulation that it offers against inconsistency due to misspecification. We present theoretical and numerical comparisons of the asymptotic variances when there is no misspecification. In addition, we derive the asymptotic variance of the AIPW estimator when there is partial misspecification. We also present a numerical robustness study that confirms the superiority of the AIPW estimator when there is misspecification.

Original languageEnglish (US)
Pages (from-to)621-630
Number of pages10
JournalStatistics and Probability Letters
Volume80
Issue number7-8
DOIs
StatePublished - Jan 13 2010

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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