Test for equality of coefficients in multivariate multiple regression
Dear Ulrich, I'll look into generalizing linear.hypothesis() so that it handles multivariate linear models. Meanwhile, vcov(x.mlm) will give you the covariance matrix of the coefficients, so you could construct your own test by ravelling coef(x.mlm) into a vector. I hope that this helps, John On Tue, 18 Jul 2006 20:15:12 +0200
Ulrich Keller <uhkeller at web.de> wrote:
Hello, suppose I have a multivariate multiple regression model such as the following:
> DF<-data.frame(x1=rep(c(0,1),each=50),x2=rep(c(0,1),50)) > tmp<-rnorm(100) > DF$y1<-tmp+DF$x1*.5+DF$x2*.3+rnorm(100,0,.5) > DF$y2<-tmp+DF$x1*.5+DF$x2*.7+rnorm(100,0,.5) > x.mlm<-lm(cbind(y1,y2)~x1+x2,data=DF) > coef(x.mlm)
y1 y2
(Intercept) 0.07800993 0.2303557
x1 0.52936947 0.3728513
x2 0.13853332 0.4604842
How can I test whether x1 and x2 respectively have the same effect on
y1
and y2? In other words, how can I test if coef(x.mlm)[2,1] is
statistically equal to coef(x.mlm)[2,2] and coef(x.mlm)[3,1] to
coef(x.mlm)[3,2]? I looked at linear.hypothesis {car} and glh.test
{gmodels}, but these do not seem the apply to multivariate models.
Thank you in advance,
Uli Keller
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-------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/