Bootstrap based model checks with missing binary response data

Gerhard Dikta, Sundarraman Subramanian, Thorsten Winkler

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Dikta, Kvesic, and Schmidt proposed a model-based resampling scheme to approximate critical values of tests for model checking involving binary response data. Their approach is inapplicable when the binary response variable is not always observed, however. We propose a missingness adjusted marked empirical process under the framework that the missing binary responses are missing at random. We introduce a resampling scheme for the bootstrap and prove its asymptotic validity. We present some numerical comparisons and illustrate our methodology using a real data set.

Original languageEnglish (US)
Pages (from-to)219-226
Number of pages8
JournalStatistics and Probability Letters
Issue number1
StatePublished - Jan 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


  • Continuous mapping theorem
  • Covariance function
  • Functional central limit theorem
  • Maximum likelihood estimator
  • Wild bootstrap


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