late.aipw {RCAL} | R Documentation |
Augmented inverse probability weighted estimation of local average treatment effects
Description
This function implements augmented inverse probability weighted (IPW) estimation of local average treatment effects (LATEs) as proposed in Tan (2006), provided the fitted instrument propensity scores and fitted values from both treatment and outcome regressions.
Usage
late.aipw(y, tr, iv, mfp, mft, mfo, off = NULL)
Arguments
y |
An |
tr |
An |
iv |
An |
mfp |
An |
mft |
An |
mfo |
An |
off |
A |
Details
The individual expectations \theta_d=E(Y(d)|D(1)>D(0))
are estimated separately for d\in\{0,1\}
using inverse probability weighting ("ipw"), treatment and outcome regressions ("or") and augmented IPW methods as proposed in Tan (2006). The population LATE is defined as \theta_1-\theta_0
.
Value
ipw |
A |
or |
A |
est |
A |
var |
The estimated variances associated with the augmented IPW estimates of |
ze |
The z-statistics for the augmented IPW estimates of |
late.est |
The augmented IPW estimate of LATE. |
late.var |
The estimated variance associated with the augmented IPW estimate of LATE. |
late.ze |
The z-statistic for the augmented IPW estimate of LATE, compared to |
References
Tan, Z. (2006) Regression and weighting methods for causal inference using instrumental variables, Journal of the American Statistical Association, 101, 1607–1618.