ATEJLTZ {drcarlate}

ATEJLTZ runs the code for ATE estimator

Description

ATEJLTZ is the version of JLTZ under full compliance.

Usage

ATEJLTZ(iMonte, dgptype, n, g, pi, iPert, iq = 0.05, iridge = 0.001, seed = 1)

Arguments

iMonte

A scalar. Monte Carlo sizes.

dgptype

A scalar. The value can be string 1, 2, or 3, respectively corresponding to the three DGP schemes in the paper (See Jiang et al. (2022) for DGP details).

n

Sample size.

g

Number of strata. The authors set g=4 in Jiang et al. (2022).

pi

Targeted assignment probability across strata.

iPert

A scalar. iPert = 0 means size. Otherwise means power: iPert is the perturbation of false null.

iq

A scalar. Size of hypothesis testing. The authors set iq = 0.05 in Jiang et al. (2022).

iridge

A scalar. The penalization parameter in ridge regression.

seed

A scalar. The random seed, the authors set seed = 1 in Jiang et al. (2022).

Value

A table summarizing the estimated results, mProd.

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

# size, iPert = 0
ATEJLTZ(iMonte = 10, dgptype = 1, n = 200, g = 4,
    pi = c(0.5, 0.5, 0.5, 0.5), iPert = 0, iq = 0.05, iridge = 0.001)

# power, iPert = 1
ATEJLTZ(iMonte = 10, dgptype = 1, n = 200, g = 4,
    pi = c(0.5, 0.5, 0.5, 0.5), iPert = 1, iq = 0.05, iridge = 0.001)