# Karlson-Holm-Breen method for comparing probit coefficients

## Usage

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.

## Description

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.

## 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.

## Examples

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

## 2. apply KHB method
with(klein15a\$variables, khb(X=X, y=Y, z="eta"))
Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred
Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred

Karlson-Holm-Breen method
Null hypothesis: Change in coefficient is not attributable to confounding by z.

p.value
pi.inv            0.5581
wst.ieq           0.0480
0               0.9535
1               0.5665
2               0.2517
3               0.4388
4               0.3487
5               0.5749
6               0.7760
7               0.3651
8               0.3345
9               0.6832
10              0.4322
11              0.4884
12              0.6036
13              0.6391