Firstly, this is my first post to Cross Validated, so apologies in advance if I have infringed any conventions.
I am writing up a PhD thesis on aspects of biomedical research, and use R for my statistics. However, I always check some of the data against another package in case I have made a coding error.
I have been running a Kruskall-Wallis test with three groups (sample sizes of 5, 8 and 9) and using Dunn's test for the post-hoc pairwise comparisons. The p-values I get for the pairwise comparisons (unadjusted for multiple comparisons) are exactly half what I get in SPSS and GraphPad for the same data. The Kruskal-Wallis p-value reported by the dunn.test package is exactly what I get running the Kruskal-Wallis test itself in R, or in SPSS and Graphpad. There is a warning after I run my code that the dunn.test package was written on a slightly later version of R, but that seems unlikely to be the cause of a factor of 2 variation. Has anyone else come across a similar discrepancy?
Best Answer
The
dunn.testpackage in R uses a one-sided test, whereas SPSS and GraphPad use two-sided tests. There is no facility in thedunn.testpackage or its functiondunn.test()to change to a two-sided test, but the p-values can be multiplied by 2 if a two-sided test is required.A two-sided Dunn's test is available from the
dunnTest()function in packageFSA(Fisheries Stock Assessment). This package is not available from CRAN, but can be downloaded by running the codesource("http://www.rforge.net/FSA/InstallFSA.R"). It requires an R version more recent than 3.0.2, and I had trouble installing it until I updated theRcpppackage from CRAN. More information on FSA can be found on https://fishr.wordpress.com/fsa/, and documentation on thedunnTest()function can be found on http://www.rforge.net/doc/packages/FSA/dunnTest.html.Thanks to Stephan Kolassa for his help in resolving this problem.