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
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