Goodness-of-fit test for randomly censored data based on maximum correlation
Authors:
- Ewa Strzalkowska-Kominiak,
- Aurea Grané
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 rightcensoring 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.
- Record ID
- CUT11bdd19ddc98460eb8f7979be0c6c71f
- Publication categories
- ;
- Author
- Journal series
- SORT-Statistics and Operations Research Transactions, ISSN 1696-2281, e-ISSN 2013-8830
- Issue year
- 2017
- Vol
- 41
- No
- 1
- Pages
- 119-138
- Other elements of collation
- schem.; tab.; wykr.; Bibliografia (na s.) - 138; Bibliografia (liczba pozycji) - [20]; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 41, Núm. 1
- Keywords in English
- Goodness-of-fit, Kaplan-Meier estimator, maximum correlation, random censoring
- DOI
- DOI:10.2436/20.8080/02.54 Opening in a new tab
- URL
- https://www.raco.cat/index.php/SORT/article/view/326052 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 25
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT11bdd19ddc98460eb8f7979be0c6c71f/
- URN
urn:pkr-prod:CUT11bdd19ddc98460eb8f7979be0c6c71f
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.