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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