## Analysis of deviance tables with Wald chi-square tests:
fm <- clm(rating ~ temp * contact, scale=~contact, data=wine)
anova(fm, type="I")
anova(fm, type="II")
anova(fm, type="III")
options(contrasts = c("contr.treatment", "contr.poly"))
m1 <- clm2(SURENESS ~ PROD, scale = ~PROD, data = soup,
link = "logistic")
## anova
anova(m1, update(m1, scale = ~.-PROD))
mN1 <- clm2(SURENESS ~ 1, nominal = ~PROD, data = soup,
link = "logistic")
anova(m1, mN1)
anova(m1, update(m1, scale = ~.-PROD), mN1)
## Fit model from polr example:
if(require(MASS)) {
fm1 <- clm2(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
anova(fm1, update(fm1, scale =~ Cont))
}
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