I have a total of 32 rats, divided into 2 groups (control and treatment group). Each group subdivided into 4 subgroups (n=4) with different treatment duration(7days, 14 days, 28days, 56 days). Lets say a parameter that i would like to observe is corneal thickness and measurements were taken every week untill each group completed their treatment duration. Hence, for 7days, i would have 32data, for 14 days= 24 data, for 28 days = 16data, 56 days = 8data.
I'm facing problems when I choose repeated measure ANOVA as there are missing data because 2 subgroups will be euthanised at every treatment time point. How can go about it? Thank you very much.
You're right, repeated measures ANOVA would not be suitable here due to the "missing" data over time. Just use a linear mixed effects model instead, here you can easily account for the missing data + the clustering/nesting of your data (i.e., corneal thickness as outcome, "treatment duration" as fixed effect, groups as categorical fixed effects and set the rats as random effects (or intercepts, you can try several different mixed effects models too and check which model is best)
Sze Min Chan Using a mixed-effects model would be an ideal choice for your scenario
Sze Min Chan If you require further assistance with your analysis, I'm here to help.
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