I'm very new to R and haven't explored repeated measures before. I have three groups (morphs: br, ye, gr), and multiple response variables that I measured over time (0hr, 1hr and 24hr). My sample sizes are low, with just 3 samples per morph per time point. The samples of the different morphs were taken from 9 individuals (col).

Variance is homogeneous for each variable, leveneTest(rfp~factor(time*morph),data=data)

but non-normal distributed looking at qqnorm for all data points per response variable (I don't know if I can and should look at this for time*morph too, though sample sizes will probably prevent this).

I would like to statistically assess differences in response variables over time within and among morphs. I believe I need to use a GLMM with repeated measures for this, but I keep going round in circles with it. I don't know how to determine which model to use, and then how to use it!

Thanks in advance

I'm very new to R and haven't explored repeated measures before. I have three groups (morphs: br, ye, gr), and multiple response variables that I measured over time (0hr, 1hr and 24hr). My sample sizes are low, with just 3 samples per morph per time point. The samples of the different morphs were taken from 9 individuals (col).

According to leveneTest(rfp~factor(time*morph),data=data), variance is homogeneous for each variable, but non-normal distributed looking at qqnorm for all data points per response variable (I don't know if I can and should look at this for time*morph too, though sample sizes will probably prevent this).

I would like to statistically assess differences in response variables over time within and among morphs. I believe I need to use a GLMM with repeated measures for this, but I keep going round in circles with it. I don't know how to determine which model to use, and then how to use it!