Note: The endpoint is CHANGE in total symptom score ("TSS"). A patient who came in "all mild" would have baseline TSS = 4, so their change ("deltaTSS") score could run from -4 to +8. An "all moderate," with baseline TSS = 8, could have a deltaTSS from -8 to +4.
This spreads the numbers out much more than current modelers are assuming. Some nice properties: the distribution will be more symmetric and likely not that far off normal. Fewer ties helps in non-parametrics.
There will be lots of data points with low leverage between -4 and +4, but significance will be won with the high-leverage data points at the extremes: Are moderates who got healthy (TSS=<-5) largely on leronlimab? Are the milds that deteriorated (TSS=>+5) largely placebo?
I not sure all modelers understand what SDs they are (or should be) assuming.
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