anova.negbin
Likelihood Ratio Tests for Negative Binomial GLMs
Method function to perform sequential likelihood ratio tests for Negative Binomial generalized linear models.
- Keywords
- regression
Usage
# S3 method for negbin
anova(object, …, test = "Chisq")Arguments
- object
Fitted model object of class
"negbin", inheriting from classes"glm"and"lm", specifying a Negative Binomial fitted GLM. Typically the output ofglm.nb().- …
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
testargument ofanova.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.
Details
This function is a method for the generic function
anova() for class "negbin".
It can be invoked by calling anova(x) for an
object x of the appropriate class, or directly by
calling anova.negbin(x) regardless of the
class of the object.
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.
References
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
See Also
Examples
# NOT RUN {
m1 <- glm.nb(Days ~ Eth*Age*Lrn*Sex, quine, link = log)
m2 <- update(m1, . ~ . - Eth:Age:Lrn:Sex)
anova(m2, m1)
anova(m2)
# }