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Optimal Scaling of Interaction Effects in Generalized Linear Models

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  • van Rosmalen, J.M.
  • Koning, A.J.
  • Groenen, P.J.F.

Abstract

Multiplicative interaction models, such as Goodman's RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are only suitable for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of interaction effects in generalized linear models with any number of categorical predictor variables. This model, which we call the optimal scaling of interactions (OSI) model, is a parsimonious, one-dimensional multiplicative interaction model. We discuss how the model can be used to visually interpret the interaction effects. Two empirical data sets are used to show how the results of the model can be applied and interpreted. Finally, several multidimensional extensions of the one-dimensional model are explored.

Suggested Citation

  • van Rosmalen, J.M. & Koning, A.J. & Groenen, P.J.F., 2007. "Optimal Scaling of Interaction Effects in Generalized Linear Models," Econometric Institute Research Papers EI 2007-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:10753
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    References listed on IDEAS

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