I didn't set the variable "treat" as ordered factor, just ordinary factor. In my example, the 3 levels of "treat" are of equal distance in the order of from a to b to c. So my understanding is that a contrast in the form of "a+c-2*b=0" was to test a linear trend of the response variable among the 3 levels of "treat". However, this linear trend also includes a special situation where a=b=c, i.e. the response variable among the 3 levels are the same, which is contrary to the linear trend conclusion and is what I want to exclude. Hope my explanation helps. Thanks
--- Ross Darnell <[EMAIL PROTECTED]> wrote: > I don't quite follow what you are trying to do but > the second contrast > has a few interpretations with the same meaning in > your case > > 1) are the 2-1 and 3-2 differences equal > 2) lack of fit of a linear trend > 3) is there a quadratic response > > If you declare your factor to be "ordered" then the > default contrasts > will be poly()nomials. > > Ross Darnell > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] > On Behalf Of array chip > Sent: Friday, 18 January 2008 10:22 AM > To: [EMAIL PROTECTED] > Subject: [R] how to specify a particular contrast > > Hi, I am running a simple one-way ANOVA with an > independent factot variable "treat" (3 levels: a, b > and c) and a response variable "y". I want to test a > linear relationship of the response among the 3 > levels > of the variable "treat" (ordered a->b->c). I used > glht() from multcomp package. Later I found out I > need > to exclude the situation where the response at the 3 > levels of "treat" are equal. I can do separate > contrasts to test them separately: > > obj<-aov(y~treat,data=dat) > ### testing a=b=c > summary(glht(obj, linfct= mcp > (treat=c('a-b=0','a-c=0','b-c=0'))),test=Ftest()) > ### testing linear relationship among a,b and c > summary(glht(obj, linfct= mcp > (treat=c('a+c-2*b=0'))),test=Ftest()) > > Is there anyway to build one contrast that tests > both > at the same time, i.e. just generate one single p > value. Because the ultimate purpose was to test the > linear relationship among the 3 levels of the > variable > "treat". Or I am asking something that is > non-sensible > to do? > > Thanks > > John Zhang > > > > > ________________________________________________________________________ > ____________ > Looking for last minute shopping deals? > > ______________________________________________ > R-help@r-project.org 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. > ____________________________________________________________________________________ Looking for last minute shopping deals? ______________________________________________ R-help@r-project.org 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.