I'm fairly new to statistics (I'm doing it for my bachelor thesis). I want to do a factorial mixed ANOVA in Jamovi, but not all of my data is homogenous (15 out of 126 measurements are not homogenous). I am able to transform the data with python, but I couldn't find any library that provides a factorial mixed ANOVA.
Experiment design: Subjects dodge virtual objects in virtual reality. I have two groups each with 15 participants. The virtual rotation for group A is amplified (e.g. they turn their head 10° in real space but 15° in virtual space). Group B has no rotation amplification. The groups are the between-subject factor. I measure their greatest turn angle in virtual space (dependent variable), while they try to dodge an incoming object. The 4 independent within-subject factors are form (3 levels), size (2 levels), speed (3 levels) and incoming_angle(7 levels).
I want to find out, if there is a difference in virtual turn angle for each group. I also want to find out, if the greater levels of each factor are causing greater turn angles.
I think because of the experiment design, I really can only go with factorial mixed ANOVA. But none of the assumptions for that method are met (normality of residuals, sphericity, homogeneity of variances).
I tried various transformations (absolute values, raising to higher powers, reciprocal, logarithmic, Box-Cox), but they all fail the assumptions.
My data looks like this: