I have a data set that looks like the following:
x1 x2 x3 x4 Weight
Factor1 1 3 10 1 4
Factor2 3 4 2 9 1
Factor3 3 5 6 1 3
Factor4 4 3 1 5 3
Factor5 5 8 4 8 2
Where x represents people and factor represents the treatment variable. The values in the first 4 columns represent risk on a scale from 1 through 10 and the weight column represents the weighted importance (1-5) of that value. I would like to create a meaningful analysis to see which x has the greatest risk based on the various factors and their weights but am unsure of how I should approach this. Since I know this is ranked data, I thought that a Friedman Test would make sense. I would also like to analyze this in R.