https://github.com/cran/MuMIn
Tip revision: 1834bb90bade3912317a15c9b7c19771f19cf6dc authored by Kamil Bartoń on 22 June 2024, 14:10:02 UTC
version 1.48.4
version 1.48.4
Tip revision: 1834bb9
model.selection.object.Rd
\name{model.selection.object}
\alias{model.selection.object}
\title{Description of Model Selection Objects}
\description{
An object of class \code{"model.selection"} holds a table of model
coefficients and ranking statistics. It is produced by \code{\link{dredge}}
or \code{\link{model.sel}}.
}
\value{
The object is a \code{data.frame} with additional attributes. Each row
represents one model. The models are ordered by the information criterion
value specified by \code{rank} (lowest on top).
Data frame columns:
\item{model terms}{For numeric covariates these columns hold coefficent value,
for factors their presence in the model. If the term is not present in a
model, value is \code{NA}. }
\item{\sQuote{varying} arguments}{optional. If any arguments differ between the
modelling function calls (except for formulas and some other arguments),
these will be held in additional columns (of class \code{"factor"}).}
\item{"df"}{Number of model parameters}
\item{"logLik"}{Log-likelihood (or quasi-likelihood for \acronym{GEE})}
\item{rank}{Information criterion value}
\item{"delta"}{\ifelse{latex}{\eqn{\Delta_{IC}}}{\enc{Δ}{Delta}_IC}}
\item{"weight"}{\sQuote{Akaike weights}.}
Attributes:
\item{model.calls}{A list containing model calls (arranged in
the same order as in the table). A model call can be retrieved with
\code{getCall(*, i)} where \var{i} is a vector of model index or name
(if given as character string). }
\item{global}{The \code{global.model} object }
\item{global.call}{Call to the \code{global.model} }
\item{terms}{A character string holding all term names. Attribute
\code{"interceptLabel"} gives the name of the intercept term. }
\item{rank}{The \code{rank} function used }
\item{beta}{A character string, representing the coefficient standardizing
method used. Either \code{"none"}, \code{"sd"} or \code{"partial.sd"}
}
\item{coefTables}{List of matrices of class \code{"coefTable"} containing
each model's coefficients with std. errors and associated \var{df}s }
\item{nobs}{Number of observations }
\item{warnings}{optional (\code{pdredge} only). A list of errors and
warnings issued by the modelling function during the fitting, with a model
number appended to each. }
Most attributes does not need (and should not) be accessed directly, use of extractor
functions is preferred. These functions include \code{getCall} for
retrieving model calls, \code{coefTable} and \code{coef} for coefficients,
and \code{nobs}. \code{logLik} extracts list of model log-likelihoods (as
\code{"logLik"} objects), and \code{Weights} extracts \sQuote{Akaike
weights}.
The object has class \code{c("model.selection", "data.frame")}.
}
\seealso{
\code{\link{dredge}}, \code{\link{model.sel}}.
}
\keyword{models}