I have two different groups, Treatment A vs Treatment B, with measurements for each individual in four different time points. That is a 2 x 4 design. The dependent variable is a discrete scale from 1 to 4 where 1 is better than 4. The fact that it is a discrete scale means that computing means and standard deviations doesn't make sense (it can't be 2.7 for instance).
Thus, the problem I have is to understand if I could use a Mixed-Factorial ANOVA to analyze whether there are differences between groups and across individuals. A colleague has suggested me to use an Ordinal Logistic Mixed Model which seems a legit approach as well. However, given the nature of the data it looks to me that a Mixed-Factorial ANOVA would be perfectly fine (it is a numeric and ordered scale, although the scale has few levels).
Furthermore, it seems that there aren't good implementations of Mixed Ordered Logit in standard software like R or SPSS for instance.
I would really appreciate if you could give me your insights about how to tackle this problem and which model is better.