abstract: the issue of how to parametrise standard log-linear model has been neglected to some extent in the literature. in this paper general aspects of parametrisation are reviewed, in close connection with linear models theory. two main alternative parametrisations, which were exclusively used by different authors, are next discussed and compared with reference to theory of multiplicative interactions in contingency tables. finally, some aspects of implementation of different parametrisations are stressed with regard to estimation procedures and possible extensions of standard log-linear model.
Coefficients of log-linear models are computed as linear combinations of the logarithms of the obser...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
The log-linear model is described as a framework for analyzing effects in multi-dimensional continge...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
The recently developed log-linear model technique for the analysis of contingency tables has many po...
<p>We compared the fit of seventeen possible models for our data, considering all combinations of si...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
Log-linear modeling is a popular statistical tool for analysing a contingency table. This presentati...
Analysis of large dimensional contingency tables is rather difficult. Fienberg and Kim (1999, Journa...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
When the highest-way association is present in a 3-way cross-classification of frequencies, standard...
Loglinear models are a useful but under-utilised research tool. One of the reasons for this is the d...
A large amount of data collected in the social sciences are counts crossclassified into categories. ...
Estimating linear-by-linear association has long been an important topic in the analysis of continge...
Consider a set of categorical variables P where at least one, denoted by Y, is binary. The log-linea...
Coefficients of log-linear models are computed as linear combinations of the logarithms of the obser...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
The log-linear model is described as a framework for analyzing effects in multi-dimensional continge...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
The recently developed log-linear model technique for the analysis of contingency tables has many po...
<p>We compared the fit of seventeen possible models for our data, considering all combinations of si...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
Log-linear modeling is a popular statistical tool for analysing a contingency table. This presentati...
Analysis of large dimensional contingency tables is rather difficult. Fienberg and Kim (1999, Journa...
The paper presents an analysis of association in a contingency table using log-linear models. The fo...
When the highest-way association is present in a 3-way cross-classification of frequencies, standard...
Loglinear models are a useful but under-utilised research tool. One of the reasons for this is the d...
A large amount of data collected in the social sciences are counts crossclassified into categories. ...
Estimating linear-by-linear association has long been an important topic in the analysis of continge...
Consider a set of categorical variables P where at least one, denoted by Y, is binary. The log-linea...
Coefficients of log-linear models are computed as linear combinations of the logarithms of the obser...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
The log-linear model is described as a framework for analyzing effects in multi-dimensional continge...