How to explain an interaction.
In this column, I have considered some simple tabular and graphical techniques that are helpful in explaining the substantive meaning of an interaction. When both of the explanatory variables are discrete, these techniques are easy to apply and provide both qualitative and quantitative interpretations of the interaction. As noted earlier, the more challenging case is one in which one or more of the explanatory variables are quantitative. One simple proposal is to construct two "reference levels" for each of the quantitative explanatory variables Then, given this set of reference levels, the explanation of the interaction can proceed along the same lines as for the case in which both explanatory variables are discrete. However, some care must be taken in the choice of reference levels.
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. fitzmaur@hsph.harvard.edu
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D004493:Education / Q000379:methods; D006801:Humans; D015233:Models, Statistical; D012016:Reference Values