khb function

Karlson-Holm-Breen method for comparing probit coefficients

Significance test for confounding; that is, the difference between regression coefficients from same-sample nested logit and probit models. The test procedure follows Karlson et al (2012), Section 3.4.

khb(X, y, z)

Arguments

• X: data frame comprising independent variables including confounding variable.
• y: vector of dependent variable.
• z: character string giving the name of the confounding variable in X.

Returns

khb returns for all model coefficients the p-value for the null hypothesis that the change in coefficients is not attributable to confounding by z.

Examples

## 1. load results from Klein (2015a)
 data(klein15a)

## 2. apply KHB method
with(klein15a$variables, khb(X=X, y=Y, z="eta"))

References

Karlson, K.B., A. Holm and R. Breen (2012). Comparing regression coefficients between same-sample nested models using logit and probit: A new method. Sociological Methodology, 42(1):286--313.

Author(s)

Thilo Klein