Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 10, 2014 erstellt
Description:
Consumer researchers seeking to explain the probability of a binary outcome in an experiment often attend to the moderation of one treatment variable's effect by the value of second. The most commonly used method for analyzing such data is logistic regression, but because this method subjects the dependent variable to a nonlinear transformation, the resulting interaction coefficients do not properly reflect moderation effects in the original probabilities. Significant moderation effects may result in non-significant interaction coefficients and vice versa. We illustrate the problem, discuss possible responses, describe how to correctly test moderation effects on probabilities, and demonstrate that addressing this problem makes a practical difference