Dear Ranjan, As you no doubt noticed, the Manova() function in the car package, or the Anova() function for which Manova() is an alias, produces type II or III tests for a multivariate linear model. To compare two nested multivariate linear models, as you wish to do, you can use the standard R anova() function -- see ?anova.mlm.
I hope this helps, John ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Mon, 19 Mar 2012 12:31:48 -0500 Ranjan Maitra <mai...@iastate.edu> wrote: > Dear colleagues, > > I had a question wrt the car package. How do I evaluate whether a > simpler multivariate regression model is adequate? > > For instance, I do the following: > > ami <- read.table(file = > "http://www.public.iastate.edu/~maitra/stat501/datasets/amitriptyline.dat";, > col.names=c("TCAD", "drug", "gender", "antidepressant","PR", "dBP", > "QRS")) > > ami$gender <- as.factor(ami$gender) > ami$TCAD <- ami$TCAD/1000 > ami$drug <- ami$drug/1000 > > > library(car) > > fit.lm <- lm(cbind(TCAD, drug) ~ gender + antidepressant + PR + dBP + > QRS, data = ami) > > fit.manova <- Manova(fit.lm) > > fit1.lm <- update(fit.lm, .~ . - PR - dBP - QRS) > > fit1.manova <- Manova(fit1.lm) > > > > Is there an easy way to find out whether the reduced model is adequate? > > I am thinking of something similar to the anova() function, I guess? > > Many thanks and best wishes, > Ranjan > > ______________________________________________ > 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. ______________________________________________ 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.
