1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
|
\name{addterm.clm2}
\alias{addterm.clm2}
\alias{dropterm.clm2}
\title{
Try all one-term additions to and deletions from a model
}
\description{
Try fitting all models that differ from the current model by adding or
deleting a single term from those supplied while maintaining
marginality.
}
\usage{
\method{addterm}{clm2}(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), \dots)
\method{dropterm}{clm2}(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), \dots)
}
\arguments{
\item{object}{
A \code{\link{clm2}} object.
}
\item{scope}{
for \code{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.
For \code{dropterm}:
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.
}
\item{scale}{
used in the definition of the AIC statistic for selecting the
models. Specifying \code{scale} asserts that the dispersion is known.
}
\item{test}{
should the results include a test statistic relative to the original
model? The Chisq test is a likelihood-ratio test.
}
\item{k}{
the multiple of the number of degrees of freedom used for the penalty.
Only \code{k=2} gives the genuine AIC: \code{k = log(n)} is sometimes referred
to as BIC or SBC.
}
\item{sorted}{
should the results be sorted on the value of AIC?
}
\item{trace}{
if \code{TRUE} additional information may be given on the fits as they are tried.
}
\item{which}{should additions or deletions occur in location or scale
models?
}
\item{\dots}{
arguments passed to or from other methods.
}}
\value{
A table of class \code{"anova"} containing columns for the change
in degrees of freedom, AIC and the likelihood ratio statistic. If
\code{test = "Chisq"} a column also contains the
p-value from the Chisq test.
}
\details{
The definition of AIC is only up to an additive constant because the
likelihood function is only defined up to an additive constant.
}
\author{Rune Haubo B Christensen}
\seealso{
\code{\link[ordinal]{clm2}}, \code{\link[=anova.clm2]{anova}},
\code{\link{addterm.default}} and \code{\link{dropterm.default}}
}
\examples{
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")
}
}
\keyword{internal}
|
