Hi JMP Community,
I routinely analyze binary outcomes such as Response / Non-Response at a single time point in my research using the Nominal Logistic Platform. Now, I need to expand my analysis to incorporate the factor of Time in my model, and I realized that I am unsure about the best approach to do so.
Specifically, in the mock data file attached to this post, I need to evaluate the effect of Time, VAR1, and VAR1 * Time for each level of VAR2 and VAR3 (see plot below), considering possible interactions between VAR1 and VAR2, and VAR1 and VAR3.
![Thierry_S_0-1645915394464.png Thierry_S_0-1645915394464.png](https://community.jmp.com/t5/image/serverpage/image-id/40330i3E502A0A3FF12C79/image-size/medium?v=v2&px=400)
![BINARY OUTCOME TIME COURSE WITH MULTIPLE EFFECTS PLOT2.png BINARY OUTCOME TIME COURSE WITH MULTIPLE EFFECTS PLOT2.png](https://community.jmp.com/t5/image/serverpage/image-id/40331i19D0146CBE535F00/image-size/medium?v=v2&px=400)
I am familiar with the Repeated Measure Least Square Means model for continuous variables, but I am struggling with the implementation of a similar approach for a Categorical outcome.
JMP 16.1, Windows
All inputs are welcome.
Best,
TS
Thierry R. Sornasse