Nos liseuses Vivlio rencontrent actuellement des problèmes de synchronisation. Nous faisons tout notre possible pour résoudre ce problème le plus rapidement possible. Toutes nos excuses pour la gêne occasionnée !
- Retrait gratuit dans votre magasin Club
- 7.000.000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
Nos liseuses Vivlio rencontrent actuellement des problèmes de synchronisation. Nous faisons tout notre possible pour résoudre ce problème le plus rapidement possible. Toutes nos excuses pour la gêne occasionnée !
- Retrait gratuit dans votre magasin Club
- 7.000.0000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
Ordered Regression Models
Parallel, Partial, and Non-Parallel Alternatives
Andrew S Fullerton, Jun Xu
64,45 €
+ 128 points
Format
Description
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 three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R.
This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable.
Web ResourceMore detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 172
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9780367737214
- Date de parution :
- 18-12-20
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 178 mm x 251 mm
- Poids :
- 589 g
