Some models proposed for the analysis of contingency tables are reviewed and illustrated with examples. These include standard loglinear models; models which are suitable for ordinal categorical variables such as ordinal loglinear, log multiplicative and logit models, and models based on an underlying distribution for the response; and models for incomplete and square tables. Estimation methods and inference are also discussed
Relational models for contingency tables are generalizations of log-linear models, allowing effects ...
AbstractThe paper considers general multiplicative models for complete and incomplete contingency ta...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
We propose a class of multiplicative models to describe the dependence of the response count on the ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complet...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
Combining theory and applications, this book presents models and methods for the analysis of two‐ an...
A comprehensive study of graphical log-linear models for contingency tables is presented. High-dimen...
Tools of algebraic statistics combined with MCMC algorithms have been used in contingency table anal...
Multidimensional contingency tables are suitable tool for capturing the count of observations of mul...
This thesis occupies with a relationship of two significant methods of analyzing multivariate contin...
Contingency tables (or cross tables) classify elements of populations or samples (of varying kinds) ...
The paper considers general multiplicative models for complete and incomplete contingency tables tha...
Relational models for contingency tables are generalizations of log-linear models, allowing effects ...
AbstractThe paper considers general multiplicative models for complete and incomplete contingency ta...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
We propose a class of multiplicative models to describe the dependence of the response count on the ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete ...
The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complet...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
Combining theory and applications, this book presents models and methods for the analysis of two‐ an...
A comprehensive study of graphical log-linear models for contingency tables is presented. High-dimen...
Tools of algebraic statistics combined with MCMC algorithms have been used in contingency table anal...
Multidimensional contingency tables are suitable tool for capturing the count of observations of mul...
This thesis occupies with a relationship of two significant methods of analyzing multivariate contin...
Contingency tables (or cross tables) classify elements of populations or samples (of varying kinds) ...
The paper considers general multiplicative models for complete and incomplete contingency tables tha...
Relational models for contingency tables are generalizations of log-linear models, allowing effects ...
AbstractThe paper considers general multiplicative models for complete and incomplete contingency ta...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...