The measured mice median weight (19.8) was statistically significantly lower than the population median weight 25g (p = 0.002, effect size r = 0.89). The mice weight value were approximately symmetrically distributed, as assessed by a histogram with superimposed density curve. Ī Wilcoxon signed-rank test was computed to assess whether the recruited mice median weight was different to the population normal median weight (25g). We’ll use the pipe-friendly function wilcox_test(). The interpretation values for r commonly in published literature are: 0.10 - = 0.5 (large effect).

Note that N corresponds to the total sample size for independent-samples test and to the total number of pairs for paired samples test.

The Z value is extracted from either coin::wilcoxsign_test() (case of one- or paired-samples test) or coin::wilcox_test() (case of independent two-samples test). The effect size r is calculated as Z statistic divided by the square root of the sample size (N) ( Z/sqrt(N)).

Calculate and report Wilcoxon test effect size (r value).

Wilcoxon signed rank test on paired samples.

In this chapter, you will learn how to compute the different types of Wilcoxon tests in R, including: Otherwise, the Wilcoxon test cannot become significant. Note that, the sample size should be at least 6.

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