Does JMP have the curvilinear logistic regression function? In my dataset, I would like to predict diagnosis of diabetes from body mass index (BMI) using logistic regression, and the quadratic model reduced the Chi-Square by 114.91, and it is a significant model. This result is from SPSS. How can I do the same analysis in JMP? Thank you!
If you are referring to having Polynomial terms for a logistic regression, JMP has that capability. Just set the degree value to the level of curvature you want to include, select the column to apply it to, and then under the "Macros", select "Polynomial to a Degree". The example below has all 2 Effects set to a quadratic polynomial
Also, I don't know what a .sav file is, so I don't know how to open it.
Thanks to Ron(below) I now know what a .sav file is.
just open the SPSS file you have in JMP
set the modeling type of Diabetes to Nominal
go to Analyze>>Fit model and set diabetes as you Y. select the z score from the list on the left an from the drop down menu choose Polynomial to degree and click Run.
then you will get the result you are looking for