I am running an analysis on repeated measures perceptual data (psychology). There are three categorical factors which specify the conditions participants viewed the stimuli in (e.g mode of viewing, length of stimus, speed of stimulus). I have also included a continuous covariate intended to meaure expertise in a particular activity (e.g years of musical training). There are no groups - all participants viewed all stimuli. The dependent variable is a continuous rating. I am a bit confused about a) checking covariate accumptions for a repeated measures design, and b) interpreting an interaction I have found between one of the factors and the covariate.

The aim is to see effects of the factors on the dependent variable controlling for the covariate (expertise).

I think the interaction means that the effect of the factor depends on the covariate and what I've done is collapse the dependent variable to only include the factor witht he interaction and make scatter plots for each level against the covariate to visualise the relatonship, but I'm not sure if this is correct/ enough. Is the presence of an interaction with the covariate a problem, perhaps implying a violation of assumptions? Or is it just a result I can report?

I have been unable to find any sources or tutorials on this - i can only find turorials on between groups or mixed designs with only one factor. Can anyone recommend sources on this kind of analysis? Or can you help me with checking covariate assumptions/ interpreting and following up covariate interactions in repeated measures designs? Also does thsi model seem reasonable?

I'm using SPSS but open to trying R/ MATLAB/ other softwares.

Thanks!