AR.test: Anderson-Rubin (1949) Test

In ivmodel: Statistical Inference and Sensitivity Analysis for Instrumental Variables Model

Anderson-Rubin (1949) Test

Description

AR.test computes the Anderson-Rubin (1949) test for the ivmodel object as well as the associated confidence interval.

Usage

AR.test(ivmodel, beta0 = 0, alpha = 0.05)

Arguments

ivmodel	ivmodel object
beta0	Null value \beta_0 for testing null hypothesis H_0: \beta = \beta_0 in ivmodel. Default is 0.
alpha	The significance level for hypothesis testing. Default is 0.05.

Value

AR.test returns a list containing the following components

Fstat	The value of the test statistic for testing the null hypothesis H_0: \beta = \beta_0 in ivmodel
df	degree of freedom for the test statistic
p.value	The p value of the test under the null hypothesis H_0: \beta = \beta_0 in ivmodel
ci	A matrix of two columns, each row contains an interval associated with the confidence interval
ci.info	A human-readable string describing the confidence interval

Author(s)

Yang Jiang, Hyunseung Kang, and Dylan Small

References

Anderson, T.W. and Rubin, H. (1949), Estimation of the parameters of a single equation in a complete system of stochastic equations, Annals of Mathematical Statistics, 20, 46-63.

See Also

See also ivmodel for details on the instrumental variables model.

Examples

data(card.data)
Y=card.data[,"lwage"]
D=card.data[,"educ"]
Z=card.data[,"nearc4"]
Xname=c("exper", "expersq", "black", "south", "smsa", "reg661", 
        "reg662", "reg663", "reg664", "reg665", "reg666", "reg667", 
		"reg668", "smsa66")
X=card.data[,Xname]
foo = ivmodel(Y=Y,D=D,Z=Z,X=X)
AR.test(foo)

ivmodel documentation built on April 9, 2023, 5:08 p.m.