Another way to do this without messing with environments is to update the
data and formula locally within the function and re-run the regression on
the updated model/data:
tukey.test <- function(m) {
ud <- data.frame( m$model, pred2=m$fitted.values^2 )
uf <- update.formula(formula(m$terms), ~ . + pred2)
summary(lm(uf, ud))$coef
}
> data(BOD)
> m1 <- lm(demand~Time,BOD)
> tukey.test(m1)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.5854086 5.0344850 2.4998403 0.0877190
Time 7.5390634 6.1271204 1.2304415 0.3062126
pred2 -0.1096744 0.1148654 -0.9548081 0.4101142
> -----Original Message-----
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Sandy Weisberg
> Sent: Wednesday, October 24, 2007 3:44 PM
> To: [EMAIL PROTECTED]
> Subject: [R] scoping problem
>
> I would like to write a function that computes Tukey's 1 df
> for nonadditivity. Here is a simplified version of the
> function I'd like to
> write: (m is an object created by lm):
>
> tukey.test <- function(m) {
> m1 <- update(m, ~.+I(predict(m)^2))
> summary(m1)$coef
> }
>
> The t-test for the added variable is Tukey's test. This won't work:
>
> data(BOD)
> m1 <- lm(demand~Time,BOD)
> tukey.test(m1)
>
> Error in predict(m) : object "m" not found
>
> This function doesn't work for two reasons:
> 1. The statement m1 <- update(m, ~.+I(predict(m)^2))
> can't see 'm' in the call to predict.
> 2. If in creating m missing values had been present,
> then predict(m), even if it could be computed, could be of
> the wrong length.
>
> Can anyone help?
>
>
>
> --
> Sanford Weisberg, [EMAIL PROTECTED]
> Office and mailing address:
> University of Minnesota, School of Statistics
> 312 Ford Hall, 224 Church St. SE, Minneapolis, MN 55455
> 612-625-8355, FAX 612-624-8868
>
> St. Paul office:
> 146 Classroom-Office Building, 612-625-8777
>
> ______________________________________________
> 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.
>
>
______________________________________________
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.
