expand.model.frame
Add new variables to a model frame
Evaluates new variables as if they had been part of the formula of the
specified model. This ensures that the same na.action
and
subset
arguments are applied and allows, for example, x
to be recovered for a model using sin(x)
as a predictor.
 Keywords
 manip, regression
Usage
expand.model.frame(model, extras, envir = environment(formula(model)), na.expand = FALSE)
Arguments
 model
 a fitted model
 extras
 onesided formula or vector of character strings describing new variables to be added
 envir
 an environment to evaluate things in
 na.expand
 logical; see below
Details
If na.expand = FALSE
then NA
values in the extra variables
will be passed to the na.action
function used in
model
. This may result in a shorter data frame (with
na.omit
) or an error (with na.fail
). If
na.expand = TRUE
the returned data frame will have precisely the
same rows as model.frame(model)
, but the columns corresponding to
the extra variables may contain NA
.
Value

A data frame.
See Also
Examples
library(stats)
model < lm(log(Volume) ~ log(Girth) + log(Height), data = trees)
expand.model.frame(model, ~ Girth) # prints data.frame like
dd < data.frame(x = 1:5, y = rnorm(5), z = c(1,2,NA,4,5))
model < glm(y ~ x, data = dd, subset = 1:4, na.action = na.omit)
expand.model.frame(model, "z", na.expand = FALSE) # = default
expand.model.frame(model, "z", na.expand = TRUE)
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