An object of class `"model.selection"`

holds a table of model
coefficients and ranking statistics. It is a 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 coeficent 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

<U+0394>_IC

‘Akaike weights’.

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 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 coefficents with std. errors and associated `df`s

Number of observations

optional (`pdredge`

only). A list of errors and
warnings issued by the modelling function during the fitting, with 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 getCall for retrieving model calls, coefTable and coef for coefficiens, 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").