I have a dataset that is survival data for 3 different treatments, single time point data (ie: % survived at end of treatment), with an n=10*3 for each treatment. This data is non-parametric, which I verified. So I have analysed difference with a Kruskal Wallis, which has in this instance given me a statistically significant p value. I though job done, not a complicated experiment, got a p value. Lovely....
However, a collaborator from a different discipline is pushing to reanalyse the data with a robust sandwich variance estimator, which I feel is innapropriate -not least because I have never seen such analysis used in similar experiments, but also because this is not-continuous data. Im not very familiar with this test at all, and am also a PhD student going up against a seasoned professor so feel out of my depth!
Would this be an appropriate use of the test, or did I get it right the first time? Any advice would be appreciated.