addterm.clm2
Try all one-term additions to and deletions from a model
Try fitting all models that differ from the current model by adding or deleting a single term from those supplied while maintaining marginality.
- Keywords
- internal
Usage
# S3 method for clm2
addterm(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), …)
# S3 method for clm2
dropterm(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), …)
Arguments
- object
A
clm2
object.- scope
for
addterm
: a formula specifying a maximal model which should include the current one. All additional terms in the maximal model with all marginal terms in the original model are tried. Fordropterm
: a formula giving terms which might be dropped. By default, the model formula. Only terms that can be dropped and maintain marginality are actually tried.- scale
used in the definition of the AIC statistic for selecting the models. Specifying
scale
asserts that the dispersion is known.- test
should the results include a test statistic relative to the original model? The Chisq test is a likelihood-ratio test.
- k
the multiple of the number of degrees of freedom used for the penalty. Only
k=2
gives the genuine AIC:k = log(n)
is sometimes referred to as BIC or SBC.- sorted
should the results be sorted on the value of AIC?
- trace
if
TRUE
additional information may be given on the fits as they are tried.- which
should additions or deletions occur in location or scale models?
- …
arguments passed to or from other methods.
Details
The definition of AIC is only up to an additive constant because the likelihood function is only defined up to an additive constant.
Value
A table of class "anova"
containing columns for the change
in degrees of freedom, AIC and the likelihood ratio statistic. If
test = "Chisq"
a column also contains the
p-value from the Chisq test.
See Also
Examples
# NOT RUN {
options(contrasts = c("contr.treatment", "contr.poly"))
if(require(MASS)) { ## dropterm, addterm, housing
mB1 <- clm2(SURENESS ~ PROD + GENDER + SOUPTYPE,
scale = ~ COLD, data = soup, link = "probit",
Hess = FALSE)
dropterm(mB1, test = "Chi") # or
dropterm(mB1, which = "location", test = "Chi")
dropterm(mB1, which = "scale", test = "Chi")
addterm(mB1, scope = ~.^2, test = "Chi", which = "location")
addterm(mB1, scope = ~ . + GENDER + SOUPTYPE,
test = "Chi", which = "scale")
addterm(mB1, scope = ~ . + AGEGROUP + SOUPFREQ,
test = "Chi", which = "location")
## Fit model from polr example:
fm1 <- clm2(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
addterm(fm1, ~ Infl + Type + Cont, test= "Chisq", which = "scale")
dropterm(fm1, test = "Chisq")
}
# }