Censored median regression and profile empirical likelihood

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Abstract

We implement profile empirical likelihood-based inference for censored median regression models. Inference for any specified subvector is carried out by profiling out the nuisance parameters from the "plug-in" empirical likelihood ratio function proposed by Qin and Tsao. To obtain the critical value of the profile empirical likelihood ratio statistic, we first investigate its asymptotic distribution. The limiting distribution is a sum of weighted chi square distributions. Unlike for the full empirical likelihood, however, the derived asymptotic distribution has intractable covariance structure. Therefore, we employ the bootstrap to obtain the critical value, and compare the resulting confidence intervals with the ones obtained through Basawa and Koul's minimum dispersion statistic. Furthermore, we obtain confidence intervals for the age and treatment effects in a lung cancer data set.

Original languageEnglish (US)
Pages (from-to)493-503
Number of pages11
JournalStatistical Methodology
Volume4
Issue number4
DOIs
StatePublished - Oct 2007

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Keywords

  • Inverse censoring weighted
  • Kaplan-Meier estimator of censoring
  • Lagrange multipliers
  • Local linearity
  • Normal approximation
  • Nuisance parameters

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