From: Ulrich Keller <uhkeller_at_web.de>

Date: Wed 19 Jul 2006 - 04:15:12 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed Jul 19 04:22:07 2006

Date: Wed 19 Jul 2006 - 04:15:12 EST

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

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed Jul 19 04:22:07 2006

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