Package: ipwErrorY 2.1

ipwErrorY: Inverse Probability Weighted Estimation of Average Treatment Effect with Misclassified Binary Outcome

An implementation of the correction methods proposed by Shu and Yi (2017) <doi:10.1177/0962280217743777> for the inverse probability weighted (IPW) estimation of average treatment effect (ATE) with misclassified binary outcomes. Logistic regression model is assumed for treatment model for all implemented correction methods, and is assumed for the outcome model for the implemented doubly robust correction method. Misclassification probability given a true value of the outcome is assumed to be the same for all individuals.

Authors:Di Shu <[email protected]>, Grace Y. Yi <[email protected]>

ipwErrorY_2.1.tar.gz
ipwErrorY_2.1.zip(r-4.5)ipwErrorY_2.1.zip(r-4.4)ipwErrorY_2.1.zip(r-4.3)
ipwErrorY_2.1.tgz(r-4.5-any)ipwErrorY_2.1.tgz(r-4.4-any)ipwErrorY_2.1.tgz(r-4.3-any)
ipwErrorY_2.1.tar.gz(r-4.5-noble)ipwErrorY_2.1.tar.gz(r-4.4-noble)
ipwErrorY_2.1.tgz(r-4.4-emscripten)ipwErrorY_2.1.tgz(r-4.3-emscripten)
ipwErrorY.pdf |ipwErrorY.html
ipwErrorY/json (API)

# Install 'ipwErrorY' in R:
install.packages('ipwErrorY', repos = c('https://shu-d.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 4 scripts 155 downloads 4 exports 1 dependencies

Last updated 6 years agofrom:92e8c2559b. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-winOKMar 31 2025
R-4.5-macOKMar 31 2025
R-4.5-linuxOKMar 31 2025
R-4.4-winOKMar 31 2025
R-4.4-macOKMar 31 2025
R-4.4-linuxOKMar 31 2025
R-4.3-winOKMar 31 2025
R-4.3-macOKMar 31 2025

Exports:Est2ReplicatesEstValidationKnownErrorKnownErrorDR

Dependencies:nleqslv