term_labels {sjlabelled} | R Documentation |
Retrieve labels of model terms from regression models
Description
This function retrieves variable labels from model terms. In case of categorical variables, where one variable has multiple dummies, variable name and category value is returned.
Usage
term_labels(
models,
mark.cat = FALSE,
case = NULL,
prefix = c("none", "varname", "label"),
...
)
get_term_labels(
models,
mark.cat = FALSE,
case = NULL,
prefix = c("none", "varname", "label"),
...
)
response_labels(models, case = NULL, multi.resp = FALSE, mv = FALSE, ...)
get_dv_labels(models, case = NULL, multi.resp = FALSE, mv = FALSE, ...)
Arguments
models |
One or more fitted regression models. May also be glm's or mixed models. |
mark.cat |
Logical, if |
case |
Desired target case. Labels will automatically converted into the
specified character case. See |
prefix |
Indicates whether the value labels of categorical variables should be prefixed, e.g. with the variable name or variable label. May be abbreviated. See 'Examples', |
... |
Further arguments passed down to |
mv , multi.resp |
Logical, if |
Details
Typically, the variable labels from model terms are returned. However,
for categorical terms that have estimates for each category, the
value labels are returned as well. As the return value is a named
vector, you can easily use it with ggplot2's scale_*()
functions to annotate plots.
Value
For term_labels()
, a (named) character vector with
variable labels of all model terms, which can be used, for instance,
as axis labels to annotate plots.
For response_labels()
,
a character vector with variable labels from all dependent variables
of models
.
Examples
# use data set with labelled data
data(efc)
fit <- lm(barthtot ~ c160age + c12hour + c161sex + c172code, data = efc)
term_labels(fit)
# make "education" categorical
if (require("sjmisc")) {
efc$c172code <- to_factor(efc$c172code)
fit <- lm(barthtot ~ c160age + c12hour + c161sex + c172code, data = efc)
term_labels(fit)
# prefix value of categorical variables with variable name
term_labels(fit, prefix = "varname")
# prefix value of categorical variables with value label
term_labels(fit, prefix = "label")
# get label of dv
response_labels(fit)
}