What to do with unequal sample sizes?

[skylandyu]

I am working on this time-effect project in which we pulled data at different time points from a big old data set. The issue is that all subjects were sacrificed at different times after treatment. So I have 16 samples at time 1, 10 samples at time 2, and so on. I am going to do Friedman test and one-way repeated measure ANOVA on those data (one for parametric and one for nonparametric). But I don't know what to do with the unequal sample size. Since my smallest group only has 4 values, SPSS only count 4 from each group when doing the analysis.

I've read about a test called Skillings-Mack Test that can be an alternative to Friedman test in this situation. But it's not available in SPSS. I've also seen something about using linear mixed model to do repeated measure ANOVA. But it seems to be a little complicated for me.

So, any advice?

 

[hlsmith]

Haven't heard of S-M, but know that multilevel models (mixed) can handle these types of data. And yes, they are very difficult.

 

[hlsmith]

Just skimmed the M-S test. The first description I saw said it can handle arbitrary missing data, that means missing at any time point. You appear to have monotonic missing data (kind of like attrition). Check this out before proceeding with M-S.