Sparser Ordinal Regression Models Based on Parametric and Additive Location‐Shift Approaches

Author:

Tutz Gerhard1,Berger Moritz2

Affiliation:

1. Institut für Statistik Ludwig‐Maximilians‐Universität München Akademiestraße 1 Munich D‐80779 Germany

2. Institut für Medizinische Biometrie, Informatik und Epidemiologie, Medizinische Fakultät Universität Bonn, Venusberg‐Campus 1 Bonn D‐53127 Germany

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference48 articles.

1. Regression models for ordinal responses: a review of methods and applications

2. ORDINAL REGRESSION MODELS FOR EPIDEMIOLOGIC DATA

3. An extended class of marginal link functions for modelling contingency tables by equality and inequality constraints;Bartolucci F.;Stat. Sin.,2007

4. Using Binary Logistic Regression Models for Ordinal Data with Non-proportional Odds

5. Berger M.(2020).orddisp: Separating location and dispersion in ordinal regression models. R package version 2.1.1.

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1. An Interpretable Neural Network-based Nonproportional Odds Model for Ordinal Regression;Journal of Computational and Graphical Statistics;2024-03-29

2. VGAM: Vector Generalized Linear and Additive Models;CRAN: Contributed Packages;2006-10-24

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