glance.ivreg: Glance at a(n) ivreg object

Description

Glance accepts a model object and returns a tibble::tibble() with exactly one row of model summaries. The summaries are typically goodness of fit measures, p-values for hypothesis tests on residuals, or model convergence information.

Glance never returns information from the original call to the modeling function. This includes the name of the modeling function or any arguments passed to the modeling function.

Glance does not calculate summary measures. Rather, it farms out these computations to appropriate methods and gathers the results together. Sometimes a goodness of fit measure will be undefined. In these cases the measure will be reported as NA.

Glance returns the same number of columns regardless of whether the model matrix is rank-deficient or not. If so, entries in columns that no longer have a well-defined value are filled in with an NA of the appropriate type.

Usage

# S3 method for ivreg
glance(x, diagnostics = FALSE, ...)

Value

A tibble::tibble() with exactly one row and columns:

adj.r.squared: Adjusted R squared statistic, which is like the R squared statistic except taking degrees of freedom into account.
df: Degrees of freedom used by the model.
df.residual: Residual degrees of freedom.
nobs: Number of observations used.
r.squared: R squared statistic, or the percent of variation explained by the model. Also known as the coefficient of determination.
sigma: Estimated standard error of the residuals.
statistic: Wald test statistic.
p.value: P-value for the Wald test.

Arguments

x

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

diagnostics

Logical indicating whether or not to return the Wu-Hausman and Sargan diagnostic information.

...

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. Two exceptions here are:

tidy() methods will warn when supplied an exponentiate argument if it will be ignored.
augment() methods will warn when supplied a newdata argument if it will be ignored.

Details

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.

Examples

Run this code

if (FALSE) { # rlang::is_installed("AER")

# 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)
}