Smoothed Empirical Likelihood Confidence Intervals for the Relative Distribution with Left-Truncated and Right-Censored Data Articles uri icon

authors

  • MOLANES LOPEZ, ELISA MARIA
  • CAO ., RICARDO
  • VAN KEILEGOM, INGRID

publication date

  • September 2010

start page

  • 453

end page

  • 473

issue

  • 3

volume

  • 38

international standard serial number (ISSN)

  • 0319-5724

abstract

  • The study of differences among groups is an interesting statistical topic in many applied fields. It is very common in this context to have data that are subject to mechanisms of loss of information, such as
    censoring and truncation. In the setting of a two-sample problem with
    data subject to left truncation and right censoring, we develop an
    empirical likelihood method to do inference for the relative
    distribution. We obtain a nonparametric generalization of Wilks' theorem
    and construct nonparametric pointwise confidence intervals for the
    relative distribution. Finally, we analyse the coverage probability and
    length of these confidence intervals through a simulation study and
    illustrate their use with a real data set on gastric cancer.