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A new model for visualizing interactions in analysis of variance

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  • Groenen, P.J.F.
  • Koning, A.J.

Abstract

In analysis of variance, there is usually little attention for interpreting the terms of the effects themselves, especially for interaction effects. One of the reasons is that the number of interaction-effect terms increases rapidly with the number of predictor variables and the number of categories. In this paper, we propose a new model, called the interaction decomposition model, that allows to visualize the interactions. We argue that with the help of the visualization, the interaction-effect terms are much easier to interpret. We apply our method to predict holiday spending1 using seven categorical predictor variables.

Suggested Citation

  • Groenen, P.J.F. & Koning, A.J., 2004. "A new model for visualizing interactions in analysis of variance," Econometric Institute Research Papers EI 2004-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1189
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    1. Siciliano, Roberta & Mooijaart, Ab, 1997. "Three-factor association models for three-way contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 24(3), pages 337-356, May.
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    3. Vartan Choulakian, 1996. "Generalized bilinear models," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 271-283, June.
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