Maximally selected statistics for the estimation of simple cutpoint models are embedded into a generalized conceptual framework based on conditional inference procedures. This powerful framework contains most of the published procedures in this area as special cases, such as maximally selected chi-squared and rank statistics, but also allows for direct construction of new test procedures for less standard test problems. As an application, a novel maximally selected rank statistic is derived from this framework for a censored response partitioned with respect to two ordered categorical covariates and potential interactions. This new test is employed to search for a high-risk group of rectal cancer patients treated with a neo-adjuvant chemoradiotherapy. Moreover, a new efficient algorithm for the evaluation of the asymptotic distribution for a large class of maximally selected statistics is given enabling the fast evaluation of a large number of cutpoints. / Series: Research Report Series / Department of Statistics and Mathematics
Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_bc2 |
Date | January 2007 |
Creators | Hothorn, Torsten, Zeileis, Achim |
Publisher | Department of Statistics and Mathematics, WU Vienna University of Economics and Business |
Source Sets | Wirtschaftsuniversität Wien |
Language | English |
Detected Language | English |
Type | Paper, NonPeerReviewed |
Format | application/pdf |
Relation | http://epub.wu.ac.at/1252/ |
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