model.selection.object: Description of Model Selection Objects

Description Value See Also

Description

An object of class "model.selection" holds a table of model coefficients and ranking statistics. It is a produced by dredge or model.sel.

Value

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:

model terms

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.

‘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 "factor").

"df"

Number of model parameters

"logLik"

Log-likelihood (or quasi-likelihood for GEE)

rank

Information criterion value

"delta"

Δ_IC

"weight"

‘Akaike weights’.

Attributes:

model.calls

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).

global

The global.model object

global.call

Call to the global.model

terms

A character string holding all term names. Attribute "interceptLabel" gives the name of intercept term.

rank

The rank function used

beta

A character string, representing the coefficient standardizing method used. Either "none", "sd" or "partial.sd"

coefTables

List of matrices of class "coefTable" containing each model's coefficents with std. errors and associated dfs

nobs

Number of observations

warnings

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").

See Also

dredge, model.sel.


MuMIn documentation built on Jan. 31, 2018, 1:03 a.m.