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Ordered Regression Models
Parallel, Partial, and Non-Parallel Alternatives
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Focusing on ordered regression models, this book delves into cumulative, stage, and adjacent classes, along with variations influenced by the parallel regression assumption. It emphasizes the benefits of using ordered regression for analyzing ordinal outcomes compared to linear and binary models. Additionally, the text provides guidance on interpreting and presenting results, supported by empirical examples from the social and behavioral sciences, making it a valuable resource for researchers in these fields.
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Ordered Regression Models, Andrew S Fullerton, Jun Xu
- Sprache
- Erscheinungsdatum
- 2016
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- Titel
- Ordered Regression Models
- Untertitel
- Parallel, Partial, and Non-Parallel Alternatives
- Sprache
- Englisch
- Autor*innen
- Andrew S Fullerton, Jun Xu
- Verlag
- CRC Press
- Erscheinungsdatum
- 2016
- Einband
- Hardcover
- Seitenzahl
- 172
- ISBN13
- 9781466569737
- Kategorie
- Wirtschaft, Mathematik, Psychologie
- Beschreibung
- Focusing on ordered regression models, this book delves into cumulative, stage, and adjacent classes, along with variations influenced by the parallel regression assumption. It emphasizes the benefits of using ordered regression for analyzing ordinal outcomes compared to linear and binary models. Additionally, the text provides guidance on interpreting and presenting results, supported by empirical examples from the social and behavioral sciences, making it a valuable resource for researchers in these fields.