ATE.ERROR: Estimating ATE with Misclassified Outcomes and Mismeasured Covariates

Addressing measurement error in covariates and misclassification in binary outcome variables within causal inference, the 'ATE.ERROR' package implements inverse probability weighted estimation methods proposed by Shu and Yi (2017, <doi:10.1177/0962280217743777>; 2019, <doi:10.1002/sim.8073>). These methods correct errors to accurately estimate average treatment effects (ATE). The package includes two main functions: ATE.ERROR.Y() for handling misclassification in the outcome variable and ATE.ERROR.XY() for correcting both outcome misclassification and covariate measurement error. It employs logistic regression for treatment assignment and uses bootstrap sampling to calculate standard errors and confidence intervals, with simulated datasets provided for practical demonstration.

Version:	1.0.0
Depends:	R (≥ 2.10)
Imports:	ggplot2, MASS, mvtnorm, rlang, stats
Suggests:	knitr, rmarkdown
Published:	2024-09-10
DOI:	10.32614/CRAN.package.ATE.ERROR
Author:	Aryan Rezanezhad [aut, cre], Grace Y. Yi [aut]
Maintainer:	Aryan Rezanezhad <Aryan.rzn at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
CRAN checks:	ATE.ERROR results

Documentation:

Reference manual:	ATE.ERROR.pdf
Vignettes:	ATE.ERROR.XY: Estimating Average Treatment Effect with Measurement Error in X and Misclassification in Y (source, R code) ATE.ERROR.Y: Function for Estimating Average Treatment Effect (ATE) with Misclassification in Y (source, R code) Naive Estimation of ATE (source, R code) True Estimation of ATE (source, R code)

Downloads:

Package source:	ATE.ERROR_1.0.0.tar.gz
Windows binaries:	r-devel: ATE.ERROR_1.0.0.zip, r-release: ATE.ERROR_1.0.0.zip, r-oldrel: ATE.ERROR_1.0.0.zip
macOS binaries:	r-release (arm64): ATE.ERROR_1.0.0.tgz, r-oldrel (arm64): ATE.ERROR_1.0.0.tgz, r-release (x86_64): ATE.ERROR_1.0.0.tgz, r-oldrel (x86_64): ATE.ERROR_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ATE.ERROR to link to this page.