Description Usage Arguments Value Author(s) References See Also Examples
Calculates the confidence interval for the effect of a treatment (endogenous) variable using an instrumental variable, which is based on an extension of Anderson-Rubin test and allows IV be possibly invalid within a certain range.
1 | ARsensitivity.ci(ivmodel, Delta=NULL, conflevel=.95)
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ivmodel |
Instrumental variable (IV) model fit using ivreg. Make sure to use the option x=TRUE when fitting the ivreg model. |
Delta |
The allowance of sensitivity parameter for possibly invalid IV. If Delta=NULL, the ARsensitivity.ci function will calculate the confidence interval for a standard Anderson-Rubin test with valid IV. |
conflevel |
Confidence level for confidence interval. |
confidence.interval |
Confidence interval for effect of treatment. If it's a 2*2 matrix, the confidence interval is consisted of two disjoint intervals, each row of the matrix is one interval. |
printinfo |
Report the confidence interval in one printing sentence. |
ci.type |
If ci.type=1, the confidence interval is finite. If ci.type=2, the confidence interval is infinite. If ci.type=3, the confidence interval is an empty set. |
Yang Jiang
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.
Jiang, Y., Zhang, N. and Small, D. (2013), Sensitivity analysis and power for instrumental variable studies, Working paper.
1 2 3 4 5 6 7 8 9 10 11 | ### a simulated data set
z = rnorm(100)
d = z+rnorm(100)
y = d+0.1*z+rnorm(100)
ivmodel = ivreg(y~d|z, x=TRUE)
### calculate confidence interval, given the allowance of sensitivity is (-0.1, 0.1)
ARsensitivity.ci(ivmodel, Delta=c(-0.1, 0.1))
### calculate confidence interval, assuming that IV is valid
ARsensitivity.ci(ivmodel)
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