On Fri, Jan 28, 2011 at 6:26 PM, Russell Pierce <rpier...@ucr.edu> wrote:
> Thanks for your response Ista,
> I'm looking at the results in newdata following your command. I agree that
> predict ran, but I don't think it did what I expect it to do. I may be
> mistaken, but shouldn't the mean of dat$out be close to the mean of
> newdata$Y? Shouldn't the values in newdata$Y (assuming predict is working
> as expected) be similar values to:
> coef(lm.res.scale)[1]+coef(lm.res.scale)[2]*newdata[,1]+coef(lm.res.scale)[3]*newdata[,2]+coef(lm.res.scale)[4]*newdata[,1]*newdata[,2]
> ?
I don't think so. The values calculated by predict.lm actually look like this:
check.predictions <- data.frame(by.hand = coef(lm.res.scale)[1]+
coef(lm.res.scale)[2]*(newdata[,1]-mean(dat[,1]))/sd(dat[,1])+
coef(lm.res.scale)[3]*(newdata[,2]-mean(dat[,2]))/sd(dat[,2])+
coef(lm.res.scale)[4]*(newdata[,1]-mean(dat[,1]))/sd(dat[,1])*(newdata[,2]-mean(dat[,2]))/sd(dat[,2]),
pre.lm = predict(lm.obj, newdata))
In other words, predict.lm assumes that the new data is on the same
scale as the original data. That is exactly what I would expect.
HTH,
Ista
> -----------------------------------
> Russell S. Pierce, M.A.
> Visual Cognition Lab
> Department of Psychology
> University of California, Riverside
> 900 University Avenue
> Riverside, CA 92521
> Lab Phone: (951) 827-7399
>
>
> On Fri, Jan 28, 2011 at 2:31 PM, Ista Zahn <iz...@psych.rochester.edu>
> wrote:
>>
>> Hi Russell,
>> There may be some subtleties that I'm not picking up on, but the
>> obvious problem is that the names of the predictors in newdata do not
>> match the names of the predictors in dat.
>>
>> names(newdata) <- names(dat)[1:2]
>> newdata$Y <- predict(lm.obj,newdata)
>>
>> does work on my machine.
>>
>> Best,
>> Ista
>>
>> On Fri, Jan 28, 2011 at 4:37 PM, Russell Pierce <rpier...@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
>> >
>> > ______________________________________________
>> > R-help@r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
>> > http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>> >
>>
>>
>>
>> --
>> Ista Zahn
>> Graduate student
>> University of Rochester
>> Department of Clinical and Social Psychology
>> http://yourpsyche.org
>
>
--
Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org
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