[R] User error in calling predict/model.frame

[Joshua Wiley]

On Sat, Jan 29, 2011 at 11:10 AM, David Winsemius
<dwinsemius at comcast.net> wrote:
>
> On Jan 29, 2011, at 12:12 PM, Russell Pierce wrote:
>
>> Just in case someone else stumbles onto this thread and is facing a
>> similar issue:  The quick solution for me turned out to be using Glm
>> and Predict in the rms package.  Thanks go to Joshua and Ista for
>> helping me out with this issue.  Double thanks go to Joshua for
>> suggesting I take a closer look at the rms package.
>>
>> library(rms)
>> dat <- data.frame(xxA = rnorm(20,10), xxB = rnorm(20,20))
>> dat$out <- with(dat,xxA+xxB+xxA*xxB+rnorm(20,20))
>> rms.res <- Glm(out ~ scale(xxA)*scale(xxB),data=dat)
>> newdata <-
>> as.data.frame(Predict(rms.res,xxA=c(-1,0,1),xxB=c(-1,0,1))[,1:3])
>
> Puzzled that you would see a particular need for the rms functions (not that
> I have anything against the rmes package, but it doesn't seem to be needed
> here.)
>
> This seems to work without error:
>
> rms.res <- glm(out ~ scale(xxA)*scale(xxB), data=dat)
> newdata <- predict(rms.res, newdata=data.frame(xxA=c(-1,0,1),xxB=c(-1,0,1)))

The issue is the predicted values are different.

#################################
require(rms)
set.seed(10)
dat <- data.frame(xxA = rnorm(20, 10), xxB = rnorm(20, 20))
dat$out <- with(dat, xxA+xxB+xxA*xxB+rnorm(20,20))

rms.res1 <- Glm(out ~ scale(xxA) * scale(xxB), data=dat)
rms.res2 <- glm(out ~ scale(xxA) * scale(xxB), data=dat)

as.data.frame(Predict(rms.res1, xxA = -1:1, xxB = -1:1))[,1:3]
predict(rms.res2, expand.grid(xxA= -1:1, xxB= -1:1))
##################################

> --
> David Winsemius, MD
> West Hartford, CT

-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/