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Causal Inference with High-Dimensional Error-Prone Covariates and Misclassified Treatments

Installation

About

We aim to deal with the average treatment effect (ATE), where the data are subject to high-dimensionality and measurement error. This package primarily contains two functions, which are used to generate artificial data and estimate ATE with high-dimensional and error-prone data accommodated.

Key Metrics

Version 0.1.5
R ≥ 3.3.1
Published 2023-05-01 350 days ago
Needs compilation? no
License GPL-3
CRAN checks CHEMIST results

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Maintainer

Maintainer

Wei-Hsin Hsu

anson60214@gmail.com

Authors

Wei-Hsin Hsu

aut / cre

Li-Pang Chen

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

CHEMIST archive

Depends

R ≥ 3.3.1
MASS

Imports

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