estimates in proc logistic when predictor is a continuous var

[sajjad1122]

Your approach is mostly correct, but a couple of things to adjust:

Intercept: You may need to reference specific threshold values for hedonic = 5 and 6 instead of using a generic intercept 1.
Category Option: The category option isn't supported in proc logistic. Use proc plm to compute predicted probabilities or adjust your estimates using the model thresholds.
This should help you get the correct predicted probabilities.

[StatDave]

The CATEGORY= option is indeed supported in PROC LOGISTIC. Perhaps you are using a much older release. If you add the E option in the ESTIMATE statement in my example below, the resulting table shows that each estimate it produces uses, in turn, one of the intercepts so that each estimate in the resulting set appropriately gives the predicted probability for one particular response level. Also, if you change LOGISTIC to GLIMMIX in the code, and run it with just the MODEL statement and add the DIST=MULT option, it runs fine without having the response in the CLASS statement.

[palolix]

Thanks for your clarification StatDave!

[SteveDenham]

With regard to GLIMMIX, I was incomplete in my assertion about including a categorical response in the CLASS statement for multinomial distributions. That only seems to be the case for a generalized logit (LINK=GLOGIT), but not for the default link for DIST=MULT, where the default is a cumulative logit.

SteveDenham

(Apologies to @StatDave )

[palolix]

Thanks for your clarification Steve!

[StatDave]

No worries, but actually GLIMMIX also runs fine with GLOGIT:

proc glimmix data=dv2; 
model dv=income/dist=mult link=glogit s; 
run;