Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for ivreg
tidy(x, conf.int = FALSE, conf.level = 0.95, instruments = FALSE, ...)
An ivreg
object created by a call to AER::ivreg()
.
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to FALSE
.
The confidence level to use for the confidence interval
if conf.int = TRUE
. Must be strictly greater than 0 and less than 1.
Defaults to 0.95, which corresponds to a 95 percent confidence interval.
Logical indicating whether to return
coefficients from the second-stage or diagnostics tests for
each endogenous regressor (F-statistics). Defaults to FALSE
.
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ...
, where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9
, all computation will
proceed using conf.level = 0.95
. Additionally, if you pass
newdata = my_tibble
to an augment()
method that does not
accept a newdata
argument, it will use the default value for
the data
argument.
This tidier currently only supports ivreg
-classed objects
outputted by the AER
package. The ivreg
package also outputs
objects of class ivreg
, and will be supported in a later release.
Other ivreg tidiers:
augment.ivreg()
,
glance.ivreg()
A tibble::tibble()
with columns:
Upper bound on the confidence interval for the estimate.
Lower bound on the confidence interval for the estimate.
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
p-value for Sargan test of overidentifying restrictions.
p-value for weak instruments test.
p-value for Wu-Hausman weak instruments test for endogeneity.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
Statistic for Sargan test of overidentifying restrictions.
Statistic for Wu-Hausman test.
Statistic for Wu-Hausman weak instruments test for endogeneity.
The standard error of the regression term.
The name of the regression term.
# feel free to ignore the following line—it allows {broom} to supply
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("AER", quietly = TRUE)) {
# load libraries for models and data
library(AER)
# load data
data("CigarettesSW", package = "AER")
# fit model
ivr <- ivreg(
log(packs) ~ income | population,
data = CigarettesSW,
subset = year == "1995"
)
# summarize model fit with tidiers
tidy(ivr)
tidy(ivr, conf.int = TRUE)
tidy(ivr, conf.int = TRUE, instruments = TRUE)
augment(ivr)
augment(ivr, data = CigarettesSW)
augment(ivr, newdata = CigarettesSW)
glance(ivr)
}
#> # A tibble: 1 × 8
#> r.squared adj.r.squared sigma statistic p.value df df.residual nobs
#> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int> <int>
#> 1 0.131 0.112 0.229 5.98 0.0184 2 46 48