Checking ANCOVA parallel slopes assumption when no degrees of freedom remain for error estimate?

Context I have the following dataset corresponding to a pilot experiment, with two treatment factors and a covariate. Factor A has 3 levels, and factor B has 2 levels. The total number of independent observations is 12. run contains the run order, trtmt corresponds to the treatment combination AB , rate is the covariate, and absorb is the response. run trtmt AB rate absorb 1 1 2 12 1.780 0.7355 2 2 4 22 1.867 0.2828 3 3 2 12 2.136 0.3884 4 4 1 11 1.952 0.6777 5 5 5 31 1.800 0.4364 6 6 1 11 2.000 0.6116 7 7 4 22 2.071 0.2929 8 8 6 32 1.951 0.6465 9 9 3 21 2.273 0.2525 10 10 3 21 2.250 0.2727 11 11 6 32 2.075 0.6707 12 12 5 31 2.158 0.3313 The resource I am using for self-study instructs the reader to plot absorb vs. rate using trtmt as the plotting symbol to see if ANCOVA is appropriate, and discuss whether treatment effects may exist. To me, the plot indicates that ANCOVA is a plausible model, though two treatment combinations seem like they may violate the parallel slopes assumption. We are then instructed to fit a one-way ANCOVA model to the data, and plot residuals against the covariate, run order, predicted values, and normal scores to check model assumptions. I omit these here, but the plots indicate model assumptions are reasonably satisfied. Where I'm stuck Normally, having checked model assumptions, I'd proceed to check the parallel slopes assumption by fitting a model with an interaction effect between the treatment factor and the covariate, then doing an ANOVA comp…