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Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives

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Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives - Fullerton, Andrew S., and Xu, Jun
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Estimate and Interpret Results from Ordered Regression Models Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption. The authors first introduce the ...

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Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives 2020, Chapman & Hall/CRC

ISBN-13: 9780367737214

Paperback

Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives 2016, CRC Press, Oxford

ISBN-13: 9781466569737

Hardcover