We occasionally utilize the coxph function in the survival library to fit multinomial logit models. (The breslow method produces the same likelihood function as the multinomial logit). We then utilize the predict function to create summary results for various combinations of covariates.  For example:

mod1<-coxph(Depvar~Price:Product+strata(ID),data=MyDCMData2,na.action=na.omit,method="breslow")

The model runs fine.

Then we create some new data that is all combinations of Price and Product and retrieve the summary linear predictors.

newdata=expand.grid(Price=factor(as.character(1:5)),Product=factor(as.character(1:5)))
## create a utility matrix for all combinations of prices and products
totalut<-predict(mod1,newdata=newdata,type="lp")

Under R 2.7.1 this produces the following output:

> totalut
          [,1]
1   0.01534582
2  -0.07628528
3  -0.88085189
4  -1.19458045
5  -1.03579684
6   0.40065672
7   0.15922492
8  -0.49233524
9  -0.65483441
10 -1.07739920
11  0.27589201
12  0.48055065
13  0.33638585
14 -0.28416678
15 -0.48762319
16  1.06071986
17  0.69041596
18  0.67479476
19  0.36360168
20 -0.09492167
21  0.66554276
22  0.55748465
23  0.37596413
24  0.01612020
25 -0.03567735
>

The problem is that under R 2.8.1 and R 2.9.1 the previous line fails with the following error:

> totalut<-predict(mod1,newdata=newdata,type="lp")
Error in model.frame.default(Terms2, newdata, xlev = object$xlevels) :
  variable lengths differ (found for 'Price')
In addition: Warning message:
'newdata' had 25 rows but variable(s) found have 43350 rows


Does anyone have an idea what is going on?

Best regards,

Michael Conklin



W. Michael Conklin
Chief Methodologist

MarketTools, Inc. | www.markettools.com<http://www.markettools.com>
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