Dear Tine, linear.hypothesis() currently has no method specifically for gls objects, and so this usage invokes the default method. I'm not sure off-hand what's appropriate for an F-test in this context (and indeed why the default test is inappropriate). Can you describe the correct test or supply a reference? I suspect that it shouldn't be hard to write a linear.hypothesis method for gls objects that fixes up the result returned by linear.hypothesis.default.
You might take a look at car:::linear.hypothesis.default to see that it does -- the computations are pretty straightforward. I hope this helps, John -------------------------------- John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Tine Huyghe > Sent: Saturday, June 16, 2007 4:19 AM > To: [email protected] > Subject: [R] linear hypothesis test in gls model > > Dear all, > > For analysis of a longitudinal data set with fixed > measurement in time I built a gls model (nlme). For testing > hypotheses in this model I used the linear.hypothesis > function from the car package. A check with the results > obtained in SAS proc MIXED with a repeated statement revealed > an inconsistency in the results. The problem can be that the > linear.hypothesis function (1) only gives the asymptotic chi > square test and/or (2) only uses the residual error. Is there > another solution to testing linear hypotheses in a gls model? > > Thanks in advance > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
