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Partitioning information in a multidimensional contingency table and centring of log‐linear parameters

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  • Jacques A. Zighera

Abstract

A centring of the parameters of a log‐linear model, based on the weighted harmonic mean of the exponential transforms of the parameters, gives results more consistent with the model than the traditional centring technique arbitrarily based—by analogy with the analysis of variance—on the average of the untransformed parameters. It permits the partitioning of the total information of the table in components of the information, each corresponding with a margin appearing in the constraints. An illustration is given at the end of the article concerning the labour force in the European Community.

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  • Jacques A. Zighera, 1985. "Partitioning information in a multidimensional contingency table and centring of log‐linear parameters," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 1(2), pages 93-108.
  • Handle: RePEc:wly:apsmda:v:1:y:1985:i:2:p:93-108
    DOI: 10.1002/asm.3150010203
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    Cited by:

    1. Valérie Girardin & Justine Lequesne & Anne Ricordeau, 2018. "Information-based Parameterization of the Log-linear Model for Categorical Data Analysis," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1105-1121, December.

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