I've run a Kruskal Wallis test, and for some of the questions the p value is not significant. Would I report this in the same way as if it was significant, stating the df, test statistic and p-value? So it would be something like this a Kruskal Wallis test was conducted but the results were found not to be significant H(3) = 2.119, p>0.05 (or would I state the exact p value here (.548))
Solved – Should I report non-significant results
kruskal-wallis test”reportingspss
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As @Germaniawerks remarked above, if you only have two groups (managers vs juniors) you should use ranksum (aka Mann-Whitney-Wilcoxon) test and there is no need for Kruskal-Wallis. If you have more than two groups, then Kruskal-Wallis will tell you if they are significantly different, but if you want to know which pairs are significantly different between each other, you need to do a post hoc comparison, e.g. ranksum test with Bonferroni correction.
Now answering specifically your question: I think your first formulation is completely acceptable.
But personally, I don't think it makes a lot of sense to report U statistic (in case of comparison between two groups, it should be U of Mann-Whitney, as explained above): few people have intuitive understanding of it, and this particular number (U=14.338) does not convey anything meaningful for the reader, only taking space. Instead, I would provide the means and standard deviations of your distributions for both groups. I would also explicitly mention the test you are doing. So taking your example I would write something along these lines:
Managers are more likely to arrive late than juniors (managers: $10 \pm 5$ minutes late, juniors: $2\pm4$ minutes late, mean$\pm$SD, $N=10$ for both groups, p<.01, Mann-Whitney-Wilcoxon ranksum test)
That's a lot of information to put inside one pair of brackets, so you can split as you like. For example you can report N in the methods section, and make a boxplot figure to illustrate the distributions. Then it would suffice to write:
Managers are more likely to arrive late than juniors, see Figure 1 (p<.01, Mann-Whitney-Wilcoxon ranksum test)
Update
Note that if your data have gross outliers, than means and SDs do not have a lot of meaning and you should rather not report them. Above I assumed that there are no gross outliers in either of the groups. Otherwise situation is more complex and maybe the best way is to provide a boxplot, without giving any numbers in the text at all.
Wikipedia appears to have your answers. Here's an excerpt from the example statement of results:
In reporting the results of a Mann–Whitney test, it is important to state:
- A measure of the central tendencies of the two groups (means or medians; since the Mann–Whitney is an ordinal test, medians are usually recommended)
- The value of U
- The sample sizes
- The significance level.
In practice some of this information may already have been supplied and common sense should be used in deciding whether to repeat it. A typical report might run,
"Median latencies in groups E and C were 153 and 247 ms; the distributions in the two groups differed significantly (Mann–Whitney U = 10.5, n1 = n2 = 8, P < 0.05 two-tailed)."
The Wilcoxon signed-rank test is appropriate for paired samples, whereas the Mann–Whitney test assumes independent samples. However, according to Field (2000), the Wilcoxon $W$ in your SPSS output is "a different version of this statistic, which can be converted into a Z score and can, therefore, be compared against critical values of the normal distribution." That explains your $z$ score too then!
FYI, Wikipedia adds that, for large samples, $U$ is approximately normally distributed. Given all these values, one can also calculate the effect size $η^2$, which in the case of Wikipedia's example is 0.319 (a calculator is implemented in section 11 here). However, this transformation of the test statistic depends on the approximate normality of $U$, so it might be inaccurate with ns = 8 (Fritz et al., 2012).
P.S. The Kruskal–Wallis test's results should not be interpreted as revealing differences between means except under special circumstances. See @Glen_b's answer to another question, "Difference Between ANOVA and Kruskal-Wallis test" for details.
References
Field, A. (2000). 3.1. Mann-Whitney test. Research Methods 1: SPSS for Windows part 3: Nonparametric tests. Retrieved from http://www.statisticshell.com/docs/nonparametric.pdf.
Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: current use, calculations, and interpretation. Journal of Experimental Psychology: General, 141(1), 2–18. PDF available via ResearchGate.
Best Answer
Yes, non-significant results are just as important as significant ones. If you are reporting any result, always include the df, test statistic, and p value. And in that case, you should state the exact p-value, rather than generalising to >0.05