Hi, I'm having trouble finding the right way to get the results I need. I have done and experiment on 20 subjects (data for #6 is missing). We have 5 sample times. There are patients who had complications and those that didn't. We have the data normalized by the 1st sample which was defined as "1". See attached data. 1) If I use the one way model doing "sample" (i.e. 1 to 5) vs NL1st (the column with the results), I get the overall model and I get the comparisons between the different sampling times (see the script in the data table). But it is not repeated measures, and it doesn't have the option to compare between those with and without complications. Note that I used both parametric and non-parametric tests because the assumption of normality in this case is suspect. 2) Thus, I should use MANOVA (I don't want to use a linear model). I transposed the data - see attached. But i'm getting lost in the details of how to run it, even after spending a couple of hours going over the support literature, and part of my problem is how to interpret the results provided, where do I find the answer to my question. I know statistics enough to understand my problem and the solutions needed, but I feel JMP takes it to a much higher level so I get a bit lost sometimes in all of the verbose output. As I said, I need the three outputs detailed below, and if someone could hand-hold me going over this i'd be very grateful: a) Are there differences between the different sampling times as a whole? If I understand correctly the way JMP works, it should be the f statistic for between groups for the "time" variable that JMP defines, right? (the groups are the 5 sampling times, not the 19 patients). If I understand correctly, the significance of the intercept is not of interest, right? b) If so, then do a comparison between the different sampling times to see where those differences are, i.e. using Tukey or Scheffe (or something else that JMP offers). I don't understand what is the results obtained when I check "test each column separately also" - what method is it using? As above, if I understand correctly, the significance of the intercept is not of interest, right? c) Separate the whole sample into those with and without complications, and compare them to see if there are significant differences between those with and without complications. In this case I don't care about which samples are the ones giving the differences, only if there are differences overall. thank you very much, Uriel.
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