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.

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#### Best Answer

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.

Thinking about C as a covariate rather than a factor may just be adding confusion.

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