[R] Predictions with missing inputs

[Bernardo Rangel Tura]

On Fri, 2011-02-11 at 20:51 -0500, Axel Urbiz wrote:
> Dear users,
> 
> I'll appreciate your help with this (hopefully) simple problem.
> 
> I have a model object which was fitted to inputs X1, X2, X3. Now, I'd like
> to use this object to make predictions on a new data set where only X1 and
> X2 are available (just use the estimated coefficients for these variables in
> making predictions and ignoring the coefficient on X3). Here's my attempt
> but, of course, didn't work.
> 
> #fit some linear model to random data
> 
> x=matrix(rnorm(100*3),100,3)
> y=sample(1:2,100,replace=TRUE)
> mydata <- data.frame(y,x)
> mymodel <- lm(y ~ ns(X1, df=3) + X2 + X3, data=mydata)
> summary(mymodel)
> 
> #create new data with 1 missing input
> 
> mynewdata <- data.frame(matrix(rnorm(100*2),100,2))
> mypred <- predict(mymodel, mynewdata)
> Thanks in advance for your help!
> 
> Axel.

Axel,

I think mice package solve your problem 

-- 
Bernardo Rangel Tura, M.D,MPH,Ph.D
National Institute of Cardiology
Brazil