I recently analyzed an experiment that manipulated 2 categorical variables and one continuous variable using ANCOVA. However, a reviewer suggested that multiple regression with the categorical variable coded as dummy variables is a more appropriate test for experiments with both categorical and continuous variables.
When is it appropriate to use ANCOVA vs. multiple regression with dummy variables and what factors should I consider in selecting between the two tests?
Thank you.
Best Answer
ttnphns is correct.
However, given your additional comments I would suggest that the reviewer wanted the change merely for interpretation. If you want to stick with ANOVA style results just call it ANOVA. ANCOVA and ANOVA are the same, as ttnphns pointed out. The difference is that with ANCOVA you don't treat the covariates as predictors and you definitely appear to want to do just that.
What the reviewer was getting at was that, while you can perform an ANOVA on continuous predictors, it's typical that one perform a regression. One feature of this is that you get estimates of the effects of the continuous variable and you can even look at interactions between it and the categorical (which aren't included in an ANCOVA but could be in an ANOVA).
You may need some help with interpretation of regression results because funny things happen on the way to interactions if you're going to use the beta values to determine the significance of your effects.