Tidy a(n) ivreg object

Source: R/aer-tidiers.R

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 cross 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,
  exponentiate = FALSE, ...)

Arguments

x

An ivreg object created by a call to AER::ivreg().
conf.int

Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.
conf.level

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.
exponentiate

Logical indicating whether or not to exponentiate the the coefficient estimates. This is typical for logistic and multinomial regressions, but a bad idea if there is no log or logit link. 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.

Value

A tibble::tibble() with one row for each term in the regression. The tibble has columns:

term

The name of the regression term.

estimate

The estimated value of the regression term.

std.error

The standard error of the regression term.

statistic

The value of a statistic, almost always a T-statistic, to use in a hypothesis that the regression term is non-zero.

p.value

The two-sided p-value associated with the observed statistic.

conf.low

The low end of a confidence interval for the regression term. Included only if conf.int = TRUE.

conf.high

The high end of a confidence interval for the regression term. Included only if conf.int = TRUE.

See also

tidy(), AER::ivreg()

Other ivreg tidiers: augment.ivreg, glance.ivreg

Examples


library(AER)
#> Error in library(AER): there is no package called ‘AER’

data("CigarettesSW", package = "AER")
#> Error in find.package(package, lib.loc, verbose = verbose): there is no package called ‘AER’
ivr <- ivreg(
  log(packs) ~ income | population,
  data = CigarettesSW,
  subset = year == "1995"
)
#> Error in ivreg(log(packs) ~ income | population, data = CigarettesSW,     subset = year == "1995"): could not find function "ivreg"

summary(ivr)
#> Error in summary(ivr): object 'ivr' not found

tidy(ivr)
#> Error in tidy(ivr): object 'ivr' not found
tidy(ivr, conf.int = TRUE)
#> Error in tidy(ivr, conf.int = TRUE): object 'ivr' not found
tidy(ivr, conf.int = TRUE, exponentiate = TRUE)
#> Error in tidy(ivr, conf.int = TRUE, exponentiate = TRUE): object 'ivr' not found

augment(ivr)
#> Error in augment(ivr): object 'ivr' not found

glance(ivr)
#> Error in glance(ivr): object 'ivr' not found