I am trying to use the predictor screening platform and though I have walked through the example on JMP, but I still have questions.
I put my response variable in a yes, no format like the example; however, when I look to see which variables are the best predictor of the response how do I interpret the results? Is the number #1 ranked variable the best for predictor for a "yes" outcome or a "no" outcome? Or is the idea that you perform this analysis and then follow up with another analysis?
Successful Outcome? | | |
Predictor | Contribution | Portion | | Rank | |
Variable1 | 4.36861 | 0.3072 | | 1 | |
Variable4 | 4.36012 | 0.3066 | | 2 | |
Variable5 | 2.29150 | 0.1612 | | 3 | |
Variable2 | 1.98570 | 0.1396 | | 4 | |
Variable3 | 1.21356 | 0.0853 | | 5 | |
I then wanted to further my analysis to see if which variable was the best predictor for a successful outcome of given a certain treatment. For this, I filtered only the data on the treatment I wanted, then excluded what I didn't want, and I reran the analysis. Would this be correct?
My final question is that the data in the example on JMP was all character nominal. Are my results accurate if my predictor variables are character ordinal or is this platform only good for character nominal data?