Comparison of cumulative link models in likelihood ratio tests. The models may differ by terms in location, scale and nominal formulae, in link, threshold function and random effect structure.
# S3 method for clm2
anova(object, ..., test = c("Chisq", "none"))
# S3 method for clmm2
anova(object, ..., test = c("Chisq", "none"))
The method returns an object of class Anova
(for printing) and
data.frame
with the following elements
character description of the cumulative link models being compared. Location, scale and nominal formulae are separated by "|"s in this order.
the residual degrees of freedom
twice the negative log likelihood (proportional to the deviance)
indication of which models are being compared.
the difference in the degrees of freedom in the models being compared, i.e. the degrees of freedom for the chi-squared test.
the likelihood ratio statistic.
the p-value from the likelihood ratio test. Absent if
test = "none"
.
a clm2
object.
one or more additional clm2
objects.
if test = "none"
the p-value for the likelihood
ratio test is suppressed.
Rune Haubo B Christensen
clm2
, addterm
,
dropterm
and
anova.default
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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