An object of class "model.selection" holds a table of model
coefficients and ranking statistics. It is produced by dredge
or model.sel.
The object is a data.frame with additional attributes. Each row
represents one model. The models are ordered by the information criterion
value specified by rank (lowest on top).
Data frame columns:
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 NA.
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 "factor").
Number of model parameters
Log-likelihood (or quasi-likelihood for GEE)
Information criterion value
the IC difference, i.e. the the relative difference to the best model, Δ_IC = IC_i - IC_min,
‘Akaike weights’, i.e. normalized model likelihoods.
Attributes:
A list containing model calls (arranged in
the same order as in the table). A model call can be retrieved with
getCall(*, i) where i is a vector of model index or name
(if given as character string).
The global.model object
Call to the global.model
A character string holding all term names. Attribute
"interceptLabel" gives the name of the intercept term.
The rank function used
A character string, representing the coefficient standardizing
method used. Either "none", "sd" or "partial.sd"
List of matrices of class "coefTable" containing
each model's coefficients with std. errors and associated dfs
Number of observations
optional (pdredge only). A list of errors and
warnings issued by the modelling function during the fitting, with a model
number appended to each.
It is not recommended to directly access the attributes. Instead, use extractor
functions if possible. These include getCall for retrieving model
calls, coefTable and coef for coefficients,
and nobs. logLik extracts list of model log-likelihoods (as
"logLik" objects), and Weights extracts ‘Akaike
weights’.
The object has class c("model.selection", "data.frame").
dredge, model.sel.