Local updating is what I would have recommended.
But predict() will work correctly with NA values in the fit if the latter
was done with na.action=na.exclude. I would find it clearer to use
fitted() here, which also works for na.action=na.exclude.
On Wed, 24 Oct 2007, Christos Hatzis wrote:
>
See:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/67474.html
and also the other posts in that thread.
On 10/24/07, Sandy Weisberg <[EMAIL PROTECTED]> wrote:
> 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 lik
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)
On 10/24/2007 3:43 PM, Sandy Weisberg wrote:
> 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)^
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