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;
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"))
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. So, changing the
order of the models would lead to difmodel.names, more fitted model objects.
For coefTable arguments that are passed to appropriate summary
method (e.g. dispersion parameter for glm may be used here).
In other functions "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.