Description Usage Arguments Author(s) References Examples
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.
1 | khb(X, y, z)
|
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 |
Thilo Klein
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.
1 2 3 4 5 |
OpenJDK 64-Bit Server VM warning: Can't detect initial thread stack location - find_vma failed
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
loan_size.add 0.9034
loan_size2.add 0.0442
lngroup_agei.add 0.0412
`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
Warning messages:
1: glm.fit: fitted probabilities numerically 0 or 1 occurred
2: glm.fit: fitted probabilities numerically 0 or 1 occurred
Warning message:
system call failed: Cannot allocate memory
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