Generalized linear modelling (GLM) is a versatile technique, which may be viewed as a generalization of well-known techniques such as least squares regression, analysis of variance, loglinear modelling, and logistic regression. In may applications, low-order interaction (such as bivariate interaction) terms are included in the model. However, as the number of categorical variables increases, the total number of low-order interactions also increases dramatically. In this papaer, we propose to constrain bivariate interactions by a bi-additive model which allows a simple graphical representation in which each category of every variable is represented by a vector.

hdl.handle.net/1765/1194
Econometric Institute Research Papers
Erasmus School of Economics

Groenen, P.J.F, & Koning, A.J. (2004). Generalized bi-additive modelling for categorical data (No. EI 2004-05). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/1194