I'm looking for a way to measure significance + variance homogeneity/heterogenity
First of all I tested my data for normality and it's not always parametrical, so I think that I should use different tests for parametrical/nonparametrical data (fig 1 and 2).
As I understood I can't use repeated measures ANOVA if I have unequal sample size so any tips would be highly apprecitated
Dear Denis,
Actually, you can use ANOVA for unequal sample size, If you data are normally distributed.
Just consider some rules for choosing post-hocs (we use them for finding the source of differences). But for your case:
* Non-equal groups: Gabriel’s or Hochberg’s GF2 are most favorites here. Hochberg’s GF2 may be better if there is a larger difference in group sizes.
* Equal variances not assumed: Games–Howell is the most commonly used here.
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It looks like you have a 4 Between x 3 Within facotrs design. Since there is only one sample (P170 14 Days in figure 2) for which the distribution is not 'normal' , and the Shapiro test is known to be biased, I would not hesitate to use a parametric ANOVA. Yet, check the distributions with histograms (especially of the p170, 14 days condition). There are non-parametric equivalents, e.g. the ARTool
and the F1_LD_F1 test from the nparLD R package.
ARTool: http://depts.washington.edu/acelab/proj/art/index.html
nparLD: https://cran.r-project.org/web/packages/nparLD/nparLD.pdf
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