Philippe Hupé
2010-Apr-08 16:03 UTC
[R] general linear hypothesis testing for manova model
Hello, I have a MANOVA model and I want to test the following hypothesis: LBM 0 where B is the parameter estimates. Is there any function to do this in R? Cheers, Philippe -- Philippe Hup? Institut Curie, CNRS UMR 144, INSERM U900 26 rue d'Ulm 75005 Paris - France Email : Philippe.Hupe at curie.fr T?l : +33 (0)1 56 24 69 91 Fax: +33 (0)1 56 24 69 11 website : http://bioinfo.curie.fr
Dear Philippe, The linear.hypothesis() function in the car package should do what you want. I hope this helps, John -------------------------------- John Fox Senator William McMaster Professor of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]On> Behalf Of Philippe Hup? > Sent: April-08-10 12:03 PM > To: R-help > Subject: [R] general linear hypothesis testing for manova model > > Hello, > > I have a MANOVA model and I want to test the following hypothesis: LBM > 0 where B is the parameter estimates. > > Is there any function to do this in R? > > Cheers, > > Philippe > > -- > Philippe Hup? > Institut Curie, CNRS UMR 144, INSERM U900 > 26 rue d'Ulm > 75005 Paris - France > > Email : Philippe.Hupe at curie.fr > T?l : +33 (0)1 56 24 69 91 > Fax: +33 (0)1 56 24 69 11 > website : http://bioinfo.curie.fr > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
Peter Dalgaard
2010-Apr-09 06:19 UTC
[R] general linear hypothesis testing for manova model
John Fox wrote:> Dear Philippe, > > The linear.hypothesis() function in the car package should do what you want. > > I hope this helps, > JohnAlso, at least in many cases, anova.mlm in the base package. The catch is that the "L" of the LBM==0 has to correspond to a linear model reduction. The "M" is the transpose of the transformation matrix (which anova.mlm calls T). -- Peter Dalgaard Center for Statistics, Copenhagen Business School Phone: (+45)38153501 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com