I have done experiments with a parasitic wasp species, comparing its life table parameters (response variables: longevity (in days), number of offspring and development time of offspring (in days)) when offered two different hosts (treatment: host 1 vs. host 2). The sample size on each host was 18-20 (some died) and the experiment was repeated four times (with a sample size of 5 each time). Since the sample size was quite small (and due to losses uneven) the resulting data are not normally distributed and heteroscedastic. To be on the safe side I used robust methods (t2way and t3way of the R package WRS2) for the analyses, e.g.:
t3way(longevity ~ treatment * sex parasitoid * run, tr = 0.2) t2way(no of offspring ~ treatment * run, tr = 0.2)
I reported the results with the values provided in the R output (effects, and p-values for the effects). Since the robust methods are hardly ever used in my field of research, they are not known and I was asked to deliver degrees of freedom, or explanations why I cannot provide them. The
t2way R-help states that no degrees of freedom are reported since an adjusted critical value is used, but I do not understand the meaning of that.
My questions are:
How do I properly report the results from both the
t2way and the
And how do I best explain the method?