drcarlate (version 1.2.0)

ATEOutput: Computes linear, nonparametric and regularized ATE estimator

Description

ATEOutput is the version of Output under full compliance.

Usage

ATEOutput(ii, tau, dgptype, rndflag, n, g, pi, iPert, iq, iridge)

Value

A list containing four matrices named vtauhat, vsighat, vstat and vdeci respectively. vtauhat is a 1x4 vector: (1) L (2) NL (3) R(dgp = 1 or 2) (4) R(dgp = 3). vsighat is a 1x4 vector: unscaled standard errors for vtauhat. vstat is a 1x4 vector: test statistic. vdeci is a 1x4 logical vector: if applicable, 1 means rejecting the null. 0 means not rejecting the null.

Arguments

ii

Monte Carlo index.

tau

A scalar. The simulated true LATE effect.

dgptype

A Scalar. 1, 2, 3 (See Jiang et al. (2022) for DGP details).

rndflag

Method of CAR (covariate-adaptive randomizations). Its value can be 1, 2, 3 or4. 1-SRS; 2-WEI; 3-BCD; 4-SBR. See Jiang et al. (2022) for more details about CAR.

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

Size of hypothesis testing. We set iq = 0.05.

iridge

A scalar. The penalization parameter in ridge regression.

Examples

ATEOutput(ii = 1, tau = 0.9122762, dgptype = 1,
        rndflag = 4, n = 2000, g = 4, pi = c(0.5,0.5,0.5,0.5),
        iPert = 1, iq = 0.05, iridge = 0.001)