tau: Compute Estimated LATE

In drcarlate: Improving Estimation Efficiency in CAR with Imperfect Compliance

Compute Estimated LATE

Description

Computes the estimated LATE in Jiang et al. (2022).

Usage

tau(muY1, muY0, muD1, muD0, A, S, Y, D, stratnum = NULL)

Arguments

muY1	A nx1 vector of hat{mu}^Y(A=1)s.
muY0	A nx1 vector of hat{mu}^Y(A=0)s.
muD1	A nx1 vector of hat{mu}^D(A=1)s.
muD0	A nx1 vector of hat{mu}^D(A=0)s.
A	A nx1 vector. Each of its elements is the treatment assignment of the corresponding observation.
S	A nx1 vector. Each of its elements is the stratum of corresponding observation.
Y	A nx1 vector. Each of its elements is the observed outcome of interest of corresponding observation.
D	A nx1 vector. Each of its elements is is a binary random variable indicating whether the individual i received treatment (Di = 1) or not (Di = 0) in the actual study.
stratnum	A nx1 vector about the unique strata numbers, the default value is NULL.

Value

A scalar. LATE estimate.

References

Jiang L, Linton O B, Tang H, Zhang Y. Improving estimation efficiency via regression-adjustment in covariate-adaptive randomizations with imperfect compliance [J]. 2022.

Examples

DGP <- FuncDGP(dgptype = 1, rndflag = 1, n = 200, g = 4, pi = c(0.5, 0.5, 0.5, 0.5))
muY1 <- DGP[["Y1"]]
muY0 <- DGP[["Y0"]]
muD1 <- DGP[["D1"]]
muD0 <- DGP[["D0"]]
A <- DGP[["A"]]
S <- DGP[["S"]]
Y <- DGP[["Y"]]
D <- DGP[["D"]]
tau(muY1, muY0, muD1, muD0, A, S, Y, D)

drcarlate documentation built on July 9, 2023, 6:16 p.m.