I have a dataset of three groups of cells treated with 10 different compounds and am not sure how to check for significant differences between those treatments. Within each group the data is also paired.
I tried doing an two-way ANOVA; however, that doesn't work because of the unbalanced sample size. I then used GLM in SPSS, which at least gives me the correct means and standard deviations for each treatment, but it doesn't calculate correct p-values since it assumes equal variances.
Could somebody suggest the correct test in this case or knows how to modify the GLM accordingly?
Edit: So here is how my dataset looks like in priciple, I only have 8 more treatments:
I now would like to compare the treatment conditions to each other, so for example 'is there a significant difference between the number of puncta in control and starvation conditions?'.
So far I used univariate GLM with the Puncta as dependent variable and group and treatment as independent factors.