Desperate help on non-normally distributed tests in JMP!

[#1]

I am fairly junior in the stats realm and am trying to figure most of this out on my own. 

My data is non-normally distributed (already ran the Shapiro Wilke normality test) and I have multiple variables I am trying to compare between 2 groups over multiple time periods with p-valves for each time period and each variable. Some of the reading I have done seems like I should run a Wilcoxon rank sum test but having trouble setting it up correctly in JMP (even with the help section online) or if anyone else knows if I should be using another type of test I would appreciate it! 

[#2]

When you say, "I have multiple variables I am trying to compare between 2 groups over multiple time periods," are you trying to see if any variable can distinguish between the groups? Also, are the time periods the same for all variables across both groups?

[#3]

I am trying to look to see if there is any difference in the variables between the 2 groups with multiple different variables but not distinguish the group. Just trying to see if there is a significant difference among the variables between the 2 groups. And the time periods are the same across all the variables. 

[#4]

You say "My data is non-normally distributed"; it is not the "data" that should be normally distributed; it is the residuals that should be normally distributed. Assuming your model is correct (sounds like it may be a repeated measures design), have you looked at the residuals? As @Mark_Bailey  said, can you elaborate on your design, data, and goals?

[#5]

See above, but I am doing a retrospective cohort study looking at group A and B and multiple measurements of echocardiography to see if I can detect differences in these measurements between the 2 groups over different time periods. 

[#6]

Ok. So, to clarify. You have two groups, A and B. Group A has n subjects, and group B has m subjects (m may or may not equal n). And each subject has multiple measurements of echocardiography (I.e., for each subject, ecg is measured at different times say t1, t2, …, tp). Do I have this correct?

[#7]

Yes, that is correct. 

[#8]

This is a classic repeated measures design. There is a lot to consider, but may I suggest you start here.

https://www.jmp.com/support/notes/30/584.html

[#9]

I am going to use Big Class as an example to illustrate one approach.

If you don't know what "Big Class" is, first go to JMP menu and click "Help", then "Sample Index", find the button in the following screenshot and click it. It will open "Big Class" data table.

Now go to JMP's Analyze menu, find "Reliability and Survival" sub-menu, then select "Life Distribution". Configure the dialog as follows:

This is to illustrate how to compare "weight" between two genders. Here is the report.

There can be different perspectives, depending how you would like to compare them, and what are important to you. From the perspective of whether the distributions of "weight" are significantly different between male and female, the result says nay.

[#10]

I am willing to try. I initially was trying to get whisker-box plots with p-values between each "box" between the 2 groups as a way to display the data. But I can try this as well!