You might use the likelihood ratio chi square (L-R ChiSquare) presented in the Effect Tests report. This quantity would serve your purpose the same way as the sum of squares for each term would in ordinary least squares linear regression:
![11964_Effect Tests Report.JPG 11964_Effect Tests Report.JPG](https://community.jmp.com/t5/image/serverpage/image-id/3362i55D765C8240D5399/image-size/medium?v=v2&px=400)
You might also use the Assess Variable Importance command in the red triangle menu for the Prediction Profiler (you have several choices of methods depending on the nature of your predictors):
![11965_Variable Importance in Prediction Profiler.JPG 11965_Variable Importance in Prediction Profiler.JPG](https://community.jmp.com/t5/image/serverpage/image-id/3363i2BD460B1F4AD0AAE/image-size/medium?v=v2&px=400)
(Thanks to my colleague, Di Michelson, for thinking of the profiler.)