Pairwise comparison of KM survival curve

[#1]

Hello JMP community,

I am currently analyzing a dataset that includes the survival of subjects under eight different diets. I conducted a log-rank test and found that there is a significant difference between at least some of the groups. Now, I want to perform post-hoc pairwise comparisons to determine which specific groups differ from one another in terms of survival.

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Attached is a file that contains an example of the data I'm trying to analyze.

can anyone help me, please?

Thanks

[#2]

I'm not sure I'm understanding completely what you're looking for, but this sounds a bit like a Reliability problem. With your data table, I used the Fit Life by X platform, assumed a Lognormal distribution, then from the nonparametric overlay plot I could see that White 2 was the only different distribution.

This isn't exactly a pairwise comparison, so I made the Estimates table into a data table and used Graph Builder to show intervals for location and scale, which is more like the pairwise comparison.

Is this what you're looking for? 

[#3]

Hi, 

thank you so much first of all, but this is not what I'm looking for.

I am interested in comparing the means of survival days between pairs of groups.

this is the plot I get from: Analyze -> Reliability and survival -> Survival -> "Y, Time to event=Survival days" -> "Grouping=Diet" 

According to the "Test between groups" there is significant deference:

My goal is to test these differences between each pair of groups (Pairwise comparison?).

I hope I'm clear now and sorry for the confusion :)

[#4]

Ah, you can do this in the Fit Y by X platform. To get the Wilcoxon (and other nonparametric) pairwise tests, select the red triangle...Nonparametric...Wilcoxon Each Pair. For more traditional (mean/stdev) pairwise comparisons, select the red triangle...Compare Means...then one of the options (usually student's t or Tukey). I've attached a script to run this to your sample table.