Nonparametric test for checking lack of fit of the quantile regression model under random censoring

Lan Wang

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

The author proposes a nonparametric test for checking the lack of fit of the quantile function of survival time given the covariates; she assumes that survival time is subjected to random right censoring. Her test statistic is a kernel-based smoothing estimator of a moment condition. The test statistic is asymptotically Gaussian under the null hypothesis. The author investigates its behavior under local alternative sequences. She assesses its finite-sample power through simulations and illustrates its use with the Stanford heart transplant data.

Original languageEnglish (US)
Pages (from-to)321-336
Number of pages16
JournalCanadian Journal of Statistics
Volume36
Issue number2
DOIs
StatePublished - Jun 1 2008

Keywords

  • Conditional moment
  • Hypothesis testing
  • Lack of fit
  • Model checking
  • Quantile regression
  • Random censoring
  • Test

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