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Not clear whether you're running one KW with 37 levels or 37 KWs (which begs several questions but here are r options for both... # install.packages("dunn.test") library(dunn.test) # using built in airquality dataset dunn.test::dunn.test(airquality$Ozone, airquality$Month, method = "holm", ...


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What I decided to go with in the end was Friedman due to the nature of the question being a non parametric one-way repeated measures test. res.fried <- myd %>% groupby(group) %>%friedman_test(y ~ time | patient) if (res.fried$p < 0.05){ print(res.fried) # friedman is significant # follow with a multiple comparisons wilcox post-hoc ...


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I think you might be able to use Friedman's test for 3 or more repeated measures. You can check out this link that shows an example: https://www.datanovia.com/en/lessons/friedman-test-in-r/. It would be even better to address the two questions in a single model. Then you would be looking into a non-parametric alternative for the two-way repeated measures ...


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