anova.negbin.RdMethod function to perform sequential likelihood ratio tests for Negative Binomial generalized linear models.
# S3 method for class 'negbin'
anova(object, ..., test = "Chisq")Fitted model object of class "negbin", inheriting from
classes "glm" and "lm", specifying a Negative Binomial
fitted GLM. Typically the output of glm.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.
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.
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.
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.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
m1 <- glm.nb(Days ~ Eth*Age*Lrn*Sex, quine, link = log)
m2 <- update(m1, . ~ . - Eth:Age:Lrn:Sex)
anova(m2, m1)
#> Likelihood ratio tests of Negative Binomial Models
#>
#> Response: Days
#> Model
#> 1 Eth + Age + Lrn + Sex + Eth:Age + Eth:Lrn + Age:Lrn + Eth:Sex + Age:Sex + Lrn:Sex + Eth:Age:Lrn + Eth:Age:Sex + Eth:Lrn:Sex + Age:Lrn:Sex
#> 2 Eth * Age * Lrn * Sex
#> theta Resid. df 2 x log-lik. Test df LR stat. Pr(Chi)
#> 1 1.90799 120 -1040.728
#> 2 1.92836 118 -1039.324 1 vs 2 2 1.403843 0.4956319
anova(m2)
#> Warning: tests made without re-estimating 'theta'
#> Analysis of Deviance Table
#>
#> Model: Negative Binomial(1.908), link: log
#>
#> Response: Days
#>
#> Terms added sequentially (first to last)
#>
#>
#> Df Deviance Resid. Df Resid. Dev Pr(>Chi)
#> NULL 145 270.03
#> Eth 1 19.0989 144 250.93 1.241e-05 ***
#> Age 3 16.3483 141 234.58 0.000962 ***
#> Lrn 1 3.5449 140 231.04 0.059730 .
#> Sex 1 0.3989 139 230.64 0.527666
#> Eth:Age 3 14.6030 136 216.03 0.002189 **
#> Eth:Lrn 1 0.0447 135 215.99 0.832601
#> Age:Lrn 2 1.7482 133 214.24 0.417240
#> Eth:Sex 1 1.1470 132 213.09 0.284183
#> Age:Sex 3 21.9746 129 191.12 6.603e-05 ***
#> Lrn:Sex 1 0.0277 128 191.09 0.867712
#> Eth:Age:Lrn 2 9.0099 126 182.08 0.011054 *
#> Eth:Age:Sex 3 4.8218 123 177.26 0.185319
#> Eth:Lrn:Sex 1 3.3160 122 173.94 0.068608 .
#> Age:Lrn:Sex 2 6.3941 120 167.55 0.040882 *
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1