Experience with Kruskal-Wallis versus Zero-Inflated Kruskal-Wallis as nonparametric alternative to one-way ANOVA I have a data set of 1 categorical predictor (4 levels) and one non-negative continuous response variable (listed as "aphidleaf in histogram). The response variable is not count data and the zeros are important. I am interested in comparing the means of the groups, and was planning a one-way ANOVA until I looked at the data.
My response variable is highly zero inflated (see frequency histogram). I have tried many transformations and have decided to use a nonparametric test. Kruskal Wallis will be straightforward and appropriate for my question to determine any difference in response variable between the treatment groups, but I found that there is a zero-inflated Kruskal Wallis test.  Does anyone have any experience with the difference between the two or any to choosing one over the other? https://github.com/chvlyl/ZIR
I know Kruskal Wallis is familiar to many people, so I wonder if it is a more widely accepted approach than the zero-inflated

Try the ZI Kruskal Wallis test. paper by Wang, Chen and Li (2021) available on MathArch. the titke is "Rank-Based Tests for Nonnegative Data with
Excessive Zeros with Applications to Microbiome Data". R code available, works well.
Good luck
SH
