Build a model selection table.
model.sel(object, ...)# S3 method for default
model.sel(object, ..., rank = NULL, rank.args = NULL,
beta = c("none", "sd", "partial.sd"), extra)
# S3 method for model.selection
model.sel(object, rank = NULL, rank.args = NULL, fit = NA,
..., beta = c("none", "sd", "partial.sd"), extra)
a fitted model object, a list of such objects, or a
"model.selection" object.
more fitted model objects.
optional, custom rank function (returning an information
criterion) to use instead of the default AICc, e.g. QAIC or BIC, may be omitted
if object is a model list returned by get.models.
optional list of arguments for the rank
function. If one is an expression, an x within it is substituted
with a current model.
logical, stating whether the model objects should be re-fitted if
they are not stored in the "model.selection" object. Set to
NA to re-fit the models only if this is needed.
See ‘Details’.
indicates whether and how the component models' coefficients
should be standardized. See the argument's description in
dredge.
optional additional statistics to include in the result,
provided as functions, function names or a list of such (best if named
or quoted). See dredge for details.
An object of class c("model.selection", "data.frame"), being a
data.frame, where each row represents one model and columns contain
useful information about each model: the coefficients, df, log-likelihood, the
value of the information criterion used,
<U+0394>_IC and ‘Akaike
weight’.
If any arguments differ between the modelling function calls, the
result will include additional columns showing them (except for formulas and
some other arguments).
See model.selection.object for its structure.
model.sel used with "model.selection" object will re-fit model
objects, unless they are stored in object (in attribute "modelList"),
if argument extra is provided, or the requested beta is different
than object's "beta" attribute, or the new rank function
cannot be applied directly to logLik objects, or new rank.args
are given (unless argument fit = FALSE).
dredge, AICc, list of supported
models.
Possible alternatives: ICtab (in package bbmle), or
aictab (AICcmodavg).
# NOT RUN {
Cement$X1 <- cut(Cement$X1, 3)
Cement$X2 <- cut(Cement$X2, 2)
fm1 <- glm(formula = y ~ X1 + X2 * X3, data = Cement)
fm2 <- update(fm1, . ~ . - X1 - X2)
fm3 <- update(fm1, . ~ . - X2 - X3)
## ranked with AICc by default
(msAICc <- model.sel(fm1, fm2, fm3))
## ranked with BIC
model.sel(fm1, fm2, fm3, rank = AIC, rank.args = alist(k = log(nobs(x))))
# or
# model.sel(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x))))
# or
# update(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x))))
# }
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