[R] after lm-fit: equality of two regression coefficients
Alexandre Galvão Patriota
alexandrepatrot at yahoo.com.br
Tue Aug 31 19:23:19 CEST 2004
Dear Christoph, You can use the package gregmisc
require(gregmisc)
C<-c(0,1,-1)
glh.test(my.lm,C)
I hope that helps
Alexandre Galvão
> Hi
>
> Let's assume, we have a multiple linear regression,
such as the one
> using the Scottish hills data (MASS, data(hills)):
>
> one dependent variable: time
> two independent var (metric): dist, climb
>
> if I am interested, after (!) fitting a lm:
>
> my. lm <- lm(time ~ dist + climb, data = hills)
>
> in the equivalence (or non-equivalence) of the two
predictors "dist"
and
> "climb":
>
> H0: dist = climb
I think you intend to ask if the *coefficients* in the
fit should be
equal, which is nonsense in this example of course.
> Is there any function in R, which lets me calculate
this, in just
giving
> the lm-object "my.lm" and e.g. a vector such as c(1,
-1),
> operationalizing the hypothesis H0: t(c(1, -1)) %*%
c(dist, climb) =
0 ?
library(car)
?linear.hypothesis
Christoph,
If you are interested in testing for b1=b2 in a
regression model, say
y=b0+b1*x1+b2*x2+e
you can compare the two models o1 and o2
o1<-lm(y~x1+x2)
o2<-lm(y~I(x1+x2))
best,
vito
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