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Ordinal Log-Linear Models for Contingency Tables

Author

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  • Brzezińska Justyna

    (University of Economics in Katowice, Faculty of Finance and Insurance, Department of Economic and Financial Analysis, 1 Maja 50, 40-287 Katowice, Poland, Poland)

Abstract

A log-linear analysis is a method providing a comprehensive scheme to describe the association for categorical variables in a contingency table. The log-linear model specifies how the expected counts depend on the levels of the categorical variables for these cells and provide detailed information on the associations. The aim of this paper is to present theoretical, as well as empirical, aspects of ordinal log-linear models used for contingency tables with ordinal variables. We introduce log-linear models for ordinal variables: linear-by-linear association, row effect model, column effect model and RC Goodman’s model. Algorithm, advantages and disadvantages will be discussed in the paper. An empirical analysis will be conducted with the use of R.

Suggested Citation

  • Brzezińska Justyna, 2016. "Ordinal Log-Linear Models for Contingency Tables," Folia Oeconomica Stetinensia, Sciendo, vol. 16(1), pages 264-273, December.
    • Handle: RePEc:vrs:foeste:v:16:y:2016:i:1:p:264-273:n:17
    DOI: 10.1515/foli-2016-0017
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    Keywords

    association models; ordinal variables; contingency table; log-linear models;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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