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)

object

a fitted model object, a list of such objects, or a
`"model.selection"`

object.

…

more fitted model objects.

rank

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`

.

rank.args

optional `list`

of arguments for the `rank`

function. If one is an expression, an `x`

within it is substituted
with a current model.

fit

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’.

beta

indicates whether and how the component models' coefficients
should be standardized. See the argument's description in
`dredge`

.

extra

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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