My study is a clinical trial with 2 treatment groups measured over 4 time points...with the outcomes assessed being blood levels.
So my independent variables are "treatment" (2 groups) and "time" (4 time points - with time being a within-subjects factor)...and my dependent variable is "blood levels".
So...I'm doing a repeated measures ANOVA (mixed model) in SPSS, but my assumption of homoscedasticity is not met.
My data meets the assumption of normality and sphericity...but not of homogeneity of variances/homoscedasticity.
I'm wondering what my best options are...given this limitation.
I've tried transformations and they haven't really helped.
I'd really appreciate any suggestions/help.
EDIT: I understand the possibility of options in my case such as: 1. repeated paired t-tests with a bonferroni correction (at the cost of loss of power) 2. non-parametric equivalents (i.e. Friedman test) to the rmANOVA ...but which is a more 'robust' test in lieu of the scientific design?