# Solved – R – Test for homogeneity of regression slopes results in singular model

I am trying to check the assumptions of a two-way ANCOVA.
So in my model I have

• two factors (F1, F2)
• one dummy coded two level covariate (C)
• one dependent variable (D)

In order to check the assumption of homogeneity of regression slopes I tried
to perform an ANOVA with type 3 sums for the model D ~ F1*F2*C to see whether any
interactions with the covariate might be significant.
Using the Anova function from the car package this corresponds to

``modd<-aov(D~F1*F2*C) Anova(modd,type=3) ``

However, I encounter the following Error message:

``Error in Anova.III.lm(mod, error, singular.ok = singular.ok, ...) :   there are aliased coefficients in the model ``

My question is, whether it makes sense for the homogeneity test to force R to compute the
ANOVA anyway by supplying the singular.ok=T option or what else I should do in order to
check the assumption.

Contents

Since C is a dummy variable with 2 levels, it really is like a factor, and your data is then a 3-factor experiment. Since there is singularity, it means that some of the cells (combinations of F1, F2, and C) are not represented in the data. Use the `table` function to find out which combinations have zero frequency, and maybe that can help you decide what might be a simpler model. And/or look at `coef(modd)` and see which coefficients are `NA`, corresponding to predictors that were thrown out.