beta.weights computes standardized coefficients (beta weights) for
a model;
coeffs extracts model coefficients;
getAllTerms extracts independent variable names from a model object;
coefTable extracts a table of coefficients, standard errors and
associated degrees of freedom when possible;
get.response extracts response variable from fitted model object;
model.names generates shorthand (alpha)numeric names for one or several
fitted models.
beta.weights(model)coeffs(model)
getAllTerms(x, ...)
## S3 method for class 'terms':
getAllTerms(x, offset = TRUE, intercept = FALSE, ...)
coefTable(model, ...)
## S3 method for class 'lme':
coefTable(model, adjustSigma, ...)
## S3 method for class 'gee':
coefTable(model, ..., type = c("naive", "robust"))
get.response(x, ...)
model.names(object, ..., labels = NULL, use.letters = FALSE)
formula.model.names enumerates the model terms in
order of their appearance in the list and in the models. Therefore changing the
order of the models leads to dimodel.names, more fitted model objects.
For coefTable arguments that are passed to appropriate vcov
or summary method (e.g. dispersion parameter for "naive" or "robust"
(summary.lme.coeffs, getAllTerms and coefTable provide
interface between the model object and model.avg (and
dredge). Custom methods can be written to provide support for
additional classes of models.