For my research, I have to compare multiple groups (between) and some factors within those groups. I will try to explain it as good as possible.

Independent variable: group. There are two groups: experts (N =13) and non-experts (N=13). These two groups evaluated 6 different robot gestures, representing emotions. They evaluated these via 6 videos. The 6 emotions represented were: anger, surprise, happiness, fear, sadness and disgust.

They received this statement for every emotion: it is feasible for a child with the Autism Spectrum Disorder to recognize this emotion.

They answered via a 7-points Likert item (1 = strongly disagree to 7 = strongly agree).

I have to compare the feasibility of the gestures within the groups (within) and for every emotion between the groups (between). I was thinking about a mixed ANOVA. Unfortunately, some data is not normally distributed (I used Shapiro-Wilk in SPSS for this because of my sample size). The emotions anger, sadness, disgust (only for non-experts) and fear (only for non-experts) are not normally distributed. I tried to fix this with transforming (log) but this did not work.

I saw something about the Generalized Estimating Equations (GEE) and the Friedman test (non-parametric tests) but I am still not really sure what to do.

I hope someone can give me some tips.