Goodness-of-fit test for randomly censored data based on maximum correlation Articles uri icon

publication date

  • January 2017

start page

  • 119

end page

  • 138

issue

  • 1

volume

  • 41

International Standard Serial Number (ISSN)

  • 1696-2281

Electronic International Standard Serial Number (EISSN)

  • 2013-8830

abstract

  • In this paper we study a goodness-of-fit test based on the maximum correlation coefficient, in the context of randomly censored data. We construct a new test statistic under general right censoring and prove its asymptotic properties. Additionally, we study a special case, when the censoring mechanism follows the well-known Koziol-Green model. We present an extensive simulation study on the empirical power of these two versions of the test statistic, showing their advantages over the widely used Pearson-type test. Finally, we apply our test to the head-and-neck cancer data.

subjects

  • Mathematics
  • Statistics

keywords

  • goodness-of-fit; kaplan-meier estimator; maximum correlation; random censoring