Likelihood Ratio Tests for Negative Binomial GLMs

DESCRIPTION:

Method function to perform sequential likelihood ratio tests for Negative Binomial generalized linear models.

USAGE:

anova.negbin(object, ..., test = "Chisq")
anova(object, ..., test = "Chisq")

REQUIRED ARGUMENTS:

object
Fitted model object of class "negbin", inheriting from classes "glm" and "lm", specifying a Negative Binomial fitted GLM. Typically the output of glm.nb().

OPTIONAL ARGUMENTS:

...
Zero or more additional fitted model objects of class "negbin". They should form a nested sequence of models, but need not be specified in any particular order.
test
Argument to match the test argument of anova.glm. Ignored (with a warning if changed) if a sequence of two or more Negative Binomial fitted model objects is specified, but possibly used if only one object is specified.

NOTE:

If only one fitted model object is specified, a sequential analysis of deviance table is given for the fitted model. The theta parameter is kept fixed. If more than one fitted model object is specified they must all be of class "negbin" and likelihood ratio tests are done of each model within the next. In this case theta is assumed to have been re-estimated for each model.

DETAILS:

This function is a method for the generic function for classnegbin . It can be invoked by calling for an objectx of the appropriate class, or directly by calling regardless of the class of the object.

SEE ALSO:

, ,

EXAMPLES:

m1 <- glm.nb(Days ~ Eth*Age*Lrn*Sex, quine, link = log)
m2 <- update(m1, . ~ . - Eth:Age:Lrn:Sex)
anova(m2, m1)
anova(m2)