ATT: IPW estimator for the Average Treatment Effect on the Treated

In pedrohcgs/IPS: IPS: Covariate Distribution Balance via Integrated Propensity Scores

Description

IPW estimator for the Average Treatment Effect on the Treated

Usage

ATT(y, d, x, ps, beta.lin.rep, trim = FALSE, trim.at = NULL, whs = NULL)

Arguments

y	An n x 1 vector of outcome of interest.
d	An n x 1 vector of binary treatment adoption indicators.
x	An n x k matrix of covariates used in the propensity score estimation
ps	An n x 1 vector of fitted propensity scores.
beta.lin.rep	An n x k matrix of estimates of the asymptotic linear representaion of the propensity score parameters (used to compute std. errors)
trim	Logical argument to whether one should trim propensity scores. Deafault is FALSE.
trim.at	Only used if trim=TRUE. If a scalar, trim all propensity score below trim.at and above 1 - trim.at. If a 2 x 1 vector, trim all propensity scores below trim.at[1] and all propensity scores above trim.at[2]. If NULL, trim.at is set to 1e-10.
whs	An optional n x 1 vector of weights to be used. If NULL, then every observation has the same weights.

Value

A list containing the following components:

att	The estimated ATT
att.se	Estimated std. error of the ATT.
att.inf	Estimated influence function of ATT estimator.

References

Sant'Anna, Pedro H. C, Song, Xiaojun, and Xu, Qi (2019), Covariate Distribution Balance via Propensity Scores, Working Paper <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3258551>.

pedrohcgs/IPS documentation built on Dec. 22, 2021, 7:39 a.m.