Hi,
Z is a three level factor variables and ZB and ZC are its corresponding binary dummy
variables. In a 'glm' of Y on Z and X, say, how do the two test specifications
test.terms = c("ZB:X","ZC:X") # and
test.terms = ~ ZB:X + ZC:X
in 'regTermTest' differ? I thought that both would return the same joint (Wald) test
for the two Z:X interactions. Why does the second one specify a 1 degree of freedom
test? The code below should help clarify my question.
Thanks much,
Danny
## I'm currently using: R Version 1.9.1 / Windows 2000 / P4/2.8 Ghz
Z <- as.factor(rep(LETTERS[1:3],20))
Y <- rep(0:1, 30)
X <- rnorm(60)
glm1 <- glm(Y ~ Z + X + Z:X, family=binomial)
summary(glm1)$coeff
regTermTest( model=glm1 , test.terms=~Z:X)
ZB <- ifelse(Z=="B",1,0)
ZC <- ifelse(Z=="C",1,0)
glm2 <- glm(Y ~ ZB + ZC + X + ZB:X + ZC:X, family=binomial)
summary(glm2)$coeff ## Okay, same as glm1
regTermTest( model=glm2 , test.terms= c("ZB:X","ZC:X"))
regTermTest( model=glm2 , test.terms= ~ ZB:X + ZC:X)
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