Hello,
This is the fitted model:
> fit
Call:
multinom(formula = resp ~ pred$cls + pred$smoke)
Coefficients:
(Intercept) pred$cls2 pred$cls3 pred$cls4 pred$cls5
pred$smoke2 pred$smoke3
Proteinuria -1.140520 0.1616644 0.05554898 -0.01584927 0.02574805
-0.4057245 -0.2898425
Hypertension -2.691215 -0.3699690 -0.22582107 0.01615898 0.26318005
0.1239051 0.2413282
Both -2.285950 -0.4473108 -0.16212932 -0.10477158 0.01272335
-0.4852405 -0.6290152
Residual Deviance: 22809.76
AIC: 22851.76
... and these, to my understanding, should be the estimated category
probabilities for a subject in the first `cls' category and 3rd
`smoke' category:
> predict(fit,
newdata=data.frame(cls=factor("1",levels=levels(pred$cls)),
+ smoke=factor("3",levels=levels(pred$smoke))),
type="probs")
Neither Proteinuria Hypertension Both
0.6715336 0.7394394 0.7247787 0.6722327
Why I am not getting probabilities? Could somebody tell me what I am
missing?
Thank you in advance,
Giovanni
--
__________________________________________________
[ ]
[ Giovanni Petris GPetris at uark.edu ]
[ Department of Mathematical Sciences ]
[ University of Arkansas - Fayetteville, AR 72701 ]
[ Ph: (479) 575-6324, 575-8630 (fax) ]
[ http://definetti.uark.edu/~gpetris/ ]
[__________________________________________________]