This paper introduces the theoretical basis of the loglinear methods, as a substitute to analysis of variance when variables are categorical, and logit, as a substitute to regression analysis in the same context. Their specific advantage is to allow the modelling of categorical, thus qualitative data, often collected from surveys, while keeping their probabilistic nature. The stress is put on the concepts of interaction and odds ratio which allow to unveil complex phenomena with nonlinear relations
This thesis occupies with a relationship of two significant methods of analyzing multivariate contin...
The Association Graph and the Multigraph for Loglinear Models will help students, particularly those...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
This paper introduces the theoretical basis of the loglinear methods, as a substitute to analysis of...
The categorized data that will be analyzed in this paper will be of the type that will use the logis...
The log-linear models and logistic regression assume two different representations of the relationsh...
"Sociologists with a quantitative bent will doubtless find it useful. . . . well-written, with a wea...
The recently developed log-linear model technique for the analysis of contingency tables has many po...
While it is common practice for researchers in psychology and other social sciences to use inferent...
Loglinear models are a useful but under-utilised research tool. One of the reasons for this is the d...
This article is in the form of a short tutorial discussion, presenting the logistic (logit)regressio...
The main objective of the study is to examine model selection methods in loglinear analysis. Log-li...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
This thesis is concerned with the analysis of cross-classified categorical data from complex sample ...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
This thesis occupies with a relationship of two significant methods of analyzing multivariate contin...
The Association Graph and the Multigraph for Loglinear Models will help students, particularly those...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...
This paper introduces the theoretical basis of the loglinear methods, as a substitute to analysis of...
The categorized data that will be analyzed in this paper will be of the type that will use the logis...
The log-linear models and logistic regression assume two different representations of the relationsh...
"Sociologists with a quantitative bent will doubtless find it useful. . . . well-written, with a wea...
The recently developed log-linear model technique for the analysis of contingency tables has many po...
While it is common practice for researchers in psychology and other social sciences to use inferent...
Loglinear models are a useful but under-utilised research tool. One of the reasons for this is the d...
This article is in the form of a short tutorial discussion, presenting the logistic (logit)regressio...
The main objective of the study is to examine model selection methods in loglinear analysis. Log-li...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
This thesis is concerned with the analysis of cross-classified categorical data from complex sample ...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
This thesis occupies with a relationship of two significant methods of analyzing multivariate contin...
The Association Graph and the Multigraph for Loglinear Models will help students, particularly those...
Logistic regression is slowly gaining acceptance in the social sciences, and fills an important nich...