Graphical regression models for polytomous variables

DOI10.1007/BF02296340zbMath1365.62449OpenAlexW1969053326MaRDI QIDQ2250645

Carolyn J. Anderson, Ulf Böckenholt

Publication date: 18 July 2014

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02296340

zbMATH Keywords

graphical modelsconditional independencemarginal maximum likelihood estimationlatent continuous variablesRC(\(M\)) association model

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Graphical methods in statistics (62A09) Applications of statistics to psychology (62P15)

Related Items

The analysis of ordered categorical data: An overview and a survey of recent developments. (With discussion), Properties of graphical regression models for multidimensional categorical data, Log-multiplicative association models as item response models

Cites Work

• Unnamed Item
• Graphical models for associations between variables, some of which are qualitative and some quantitative
• The analysis of cross-classified data having ordered and/or unordered categories: Association models, correlation models, and asymmetry models for contingency tables with or without missing entries
• Distance between populations using mixed continuous and categorical variables
• Mixtures of Continuous and Categorical Variables in Discriminant Analysis
• A Random-Effects Ordinal Regression Model for Multilevel Analysis
• Multivariate Two Sample Tests with Dichotomous and Continuous Variables. I. The Location Model
• Multivariate Correlation Models with Mixed Discrete and Continuous Variables