[R] predict from a multiple regression model

[Chuck Cleland]

On 1/22/2008 9:50 AM, Fränzi 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
> 
> Fränzi
> 
>  
> 
>  
> 
> ************************************************************************
> 
> Dr. Fränzi Korner-Nievergelt
> 
> oikostat - Statistische Analysen und Beratung
> 
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> 
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-- 
Chuck Cleland, Ph.D.
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