I have three dichotomous nominal independent variables and one four-level nominal dependent variable. The dependent variable is measured multiple times (either 3 or 4, randomly determined) per configuration of IV conditions. All data is within-subjects; that is, every subject experiences each configuration of IV conditions exactly once.
Is it even possible to run a multinomial regression given the repeated measures and multiple measurements? Or should I instead dummy code the DV into three binary variables, and either run a series of binary logistic regressions or average each of the binary variables across each config of conditions and run a multivariate multiple linear regression? (For the record, I have actually performed this dummy coding, and it results in a significant amount of missing data due to the rarity of two of the four DV levels - at least half the subjects would need to be excluded. I'd like to avoid this if possible - are there any alternatives?)
If I should run logistic regressions (either a single multinomial regression or a series of binary regressions), are there any resources for how to run such a test in common statistical software packages (R, SPSS, SAS, HLM, etc.) that touch on analyzing repeated measures data with multiple IVs and multiple measurements per condition?