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

[Ista Zahn]

Hi Russell,
There may be some subtleties that I'm not picking up on, but the
obvious problem is that the names of the predictors in newdata do not
match the names of the predictors in dat.

names(newdata) <- names(dat)[1:2]
   newdata$Y <- predict(lm.obj,newdata)

does work on my machine.

Best,
Ista

On Fri, Jan 28, 2011 at 4:37 PM, Russell Pierce <rpier001 at ucr.edu> wrote:
> I want to predict values from an existing lm (linear model, e.g.
> lm.obj) result in R using a new set of predictor variables (e.g.
> newdata).  However, it seems that because my linear models was made by
> calling scale() on the target predictor that predict exits with an
> error, "Error in scale(xxA, center = 9.7846094491829, scale =
> 0.959413568556403) : object 'xxA' not found".  By debugging predict, I
> can see that the error occurs in a call to model.frame.  By debugging
> model frame I can see the error occurs with this command:  variables
> <- eval(predvars, data, env); it seems likely that the error is
> because predvars looks like this:
>
>    list(scale(xxA, center = 10.2058714830537, scale = 0.984627257169526),
>    scale(xxB, center = 20.4491690881149, scale = 1.13765718273923))
>
> An example case:
>
>    dat <- data.frame(xxA = rnorm(20,10), xxB = rnorm(10,20))
>    dat$out <- with(dat,xxA+xxB+xxA*xxB+rnorm(20,20))
>    xVar <- "scale(xxA)"
>    traceVar <- "scale(xxB)"
>    DVname <- "out"
>    lm.obj <- lm.res.scale <- lm(out ~ scale(xxA)*scale(xxB),data=dat)
>    my.data <- lm.obj$model #load the data from the lm object
>    X1 <- my.data[,xVar]
>    X2 <- my.data[,traceVar]
>    DV <- lm.obj$model[,DVname]
>    newdata <- expand.grid(X1=c(-1,0,1),X2=c(-1,0,1))
>    newdata$X1 <- newdata$X1 * sd(my.data[,xVar])
>    newdata$X2 <- newdata$X2 * sd(my.data[,traceVar])
>    names(newdata) <- c(xVar,traceVar) #have to rename to original
> variable names for predict to work
>    newdata$Y <- predict(lm.obj,newdata)
>
> Is there something I could do before passing newdata or lm.obj to
> predict() that would prevent the error?  From the help file it looks
> like I might be able to do something with the terms, argument but I
> haven't quite figured out what I would need to do. Alternatively, is
> there a fix for model.frame that would prevent the error?  Should
> predict() behave this way?
>
> Thanks for your time,
>
> Russell S. Pierce
>
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-- 
Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org