URV's Author/s: Grané, Aurea Strzalkowska-Kominiak, Ewa

Keywords: Goodness-of-fit, Kaplan-Meier estimator, maximum correlation, random censoring

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 ad- vantages over the widely used Pearson-type test. Finally, we apply our test to the head-and-neck cancer data.

Journal publication year: 2017

Publication Type: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article