MuMIn (version 1.15.6)

model.selection.object: Description of Model Selection Objects


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:

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").


Number of model parameters


Log-likelihood (or quasi-likelihood for GEE)


Information criterion value




‘Akaike weights’.



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 ""


List of matrices of class "coefTable" containing each model's coefficents 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 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.