FAQ/kw242018-01-05 12:45:54PeterWatson232014-01-22 15:40:16PeterWatson222013-08-20 15:12:28PeterWatson212013-05-31 09:14:50PeterWatson202013-05-13 11:19:29PeterWatson192013-03-08 10:17:31localhostconverted to 1.6 markup182011-08-02 14:04:55PeterWatson172011-08-02 13:55:20PeterWatson162011-08-01 15:52:39PeterWatson152011-07-22 10:09:23PeterWatson142011-07-22 10:07:12PeterWatson132011-07-22 10:06:52PeterWatson122011-07-20 14:07:57PeterWatson112007-08-16 12:25:31PeterWatson102007-01-25 15:52:51PeterWatson92006-08-15 15:51:27PeterWatson82006-08-15 15:47:51PeterWatson72006-08-15 15:45:08PeterWatson62006-08-15 15:42:11PeterWatson52006-08-15 15:32:25PeterWatson42006-08-15 11:36:09PeterWatson32006-08-15 11:35:37PeterWatson22006-08-15 11:34:47PeterWatson12006-08-15 11:28:06PeterWatsonPost-hoc nonparametric pairwise comparisons between groupsAs of Release 18, the new NPTESTS procedure offers Dunn's post hoc tests for the Kruskal-Wallis omnibus test. In the menus, select Analyze>Nonparametric Tests>Independent Samples. You will get a Kruskal-Wallis test and post hoc tests automatically if the omnibus test is significant if you specify a grouping variable with more than two levels and one or more test or response variables that are defined as having measurement scale levels of Scale. Field (2013) gives some examples of post-hocs in SPSS. No procedure exists, however, in SPSS (upto version 17) for performing post-hoc pairwise group comparisons when the Kruskal-Wallis nonparametric test is used. Kruskal-Wallis compares three or more groups and is the nonparametric analogue of the on-way anova. It is recommended by Lantz (2013) for analysis of non-Normal group data. The below syntax and this EXCEL spreadsheet implement procedures for performing nonparametric post-hoc tests on independent samples suggested by Sprent and Smeeton (2001) and Conover (1999). To guard against false positive results Sprent and Smeeton suggest only specific comparisons should be tested and only if the overall Kruskal-Wallis test is significant (as in the LSD approach for t-tests). The results from this method are very similar to the method of Conover(1999). Both these methods are liberal in detecting pairwise group differences. The spreadsheet performs all possible pairwise post-hoc comparisons for upto 500 observations in total and upto 10 groups. As a further precaution Bonferroni, Sidak, Holm or Ryan adjustments to outputted p-values could be used. In particular other authors suggest using these corrections on pairwise Mann-Whitney tests. For further details on these adjustments see the Graduate Statistics Seminar on post-hoc tests. Sokal and Rohlfe (1995) proposed a test of all pairwise post-hoc comparisons using a Tukey correction which, is consequently, much more conservative than the Conover and Sprent and Smeeton tests which are better for subsets of pairwise comparisons. After opening a spreadsheet containing y (response) and group columns you can run the SPSS Macro syntax below: [COPY AND PASTE INTO A SPSS SYNTAX WINDOW, SELECT ALL AND RUN; SPECIFY TWO GROUPS TO BE COMPARED IN LAST LINE] SPSS syntax to output raw group means corresponding to mean ranks just obtained by !kwpairs References Conover WJ (1999) Practical nonparametric statistics. 3rd Edition. Wiley:New York. Field A (2013) Discovering statistics using IBM SPSS Statistics. Fourth Edition. Sage:London. Lantz B (2013) The impact of sample non-normality on ANOVA and alternative methods. British Journal of Mathematical and Statistical Psychology 66(2) 224-244. This paper recommends the use of Kruskal-Wallis tests over other tests as it is particularly sensitive to picking up group differences between non-Normal populations. Sokal RR & Rohlf FJ (1995) Biometry:the principles and practice of statistics in biological research. 3rd Edition. WH Freeman:New York. Sprent P & Smeeton NC (2001) Applied nonparametric statistical methods. 3rd Edition. Chapman and Hall:London.