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:
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-4.4-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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:92e8c2559b. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | OK | Nov 01 2024 |
| R-4.5-linux | OK | Nov 01 2024 |
| R-4.4-win | OK | Nov 01 2024 |
| R-4.4-mac | OK | Nov 01 2024 |
| R-4.3-win | OK | Nov 01 2024 |
| R-4.3-mac | OK | Nov 01 2024 |
Exports:Est2ReplicatesEstValidationKnownErrorKnownErrorDR
Dependencies:nleqslv
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Inverse Probability Weighted (IPW) Estimation of Average Treatment Effect (ATE) with Misclassified Binary Outcome | ipwErrorY-package |
| Estimation of ATE with Two Replicates | Est2Replicates |
| Estimation of ATE with Validation Data | EstValidation |
| Estimation of ATE with Known Error | KnownError |
| Doubly Robust Estimation of ATE with Known Error | KnownErrorDR |
