On 1/22/2008 9:50 AM, Fr?nzi Korner wrote:> Hello
>
>
>
> how can I predict from a lm-object over a range of values of one
explanatory
> variable without having to specify values for all the other explanatory
> variables?
>
>
>
> e.g.
>
>
>
> mod<-lm(y~x1+x2+x3+x4)
>
>
>
> x1.new<-seq(0, 100)
>
> predict(mod, new=list(x1=x1.new))
>
>
>
>
>
> Here, predict() does not work, since values for x2, x3 and x4 are missing.
> Is there a function or argument that, in such a case, averages or weights
> over the other explanatory variables, how it is done in Genstat?
You might consider effect() in the effects package by John Fox. For
example:
library(effects)
mod.pres <- lm(prestige ~ log(income, 10) + poly(education, 3) +
poly(women, 2), data=Prestige)
effect("poly(women,2)", mod.pres, xlevels=list(women = seq(0,100,20)))
poly(women,2) effect
women
0 20 40 60 80 100
47.71028 45.12385 44.53749 45.95121 49.36499 54.77883
> Thanks
>
> Fr?nzi
>
>
>
>
>
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> Dr. Fr?nzi Korner-Nievergelt
>
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