TUTZ, G (1991) SEQUENTIAL MODELS IN CATEGORICAL REGRESSION. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 11 (3). pp. 275-295. ISSN 0167-9473,
Full text not available from this repository.Abstract
Threshold models for ordered categorical data as considered by McCullagh (1980) have become a standard tool in categorical regression. Alternatively, the class of sequential models is considered where response categories are reached successively step by step. The sequential models are derived from assumptions about an underlying stepwise response mechanism. Connections between the McCullagh type models and the sequential models are investigated. Several examples are considered where the computing has been done by a new program package which includes ordinal regression models. Thereby it is shown that sequential models are appropriate tools which widen the scope of ordered categorical regression.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | GENERALIZED LINEAR-MODELS; ORDINAL DATA; LIFE; ORDERED CATEGORICAL REGRESSION; THRESHOLD MODELS; SEQUENTIAL MODELS; GROUPED COX MODEL; PROPORTIONAL HAZARDS MODEL |
| Depositing User: | Dr. Gernot Deinzer |
| Last Modified: | 19 Oct 2022 08:46 |
| URI: | https://pred.uni-regensburg.de/id/eprint/55011 |
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