Package: SOR 0.23.1
SOR: Estimation using Sequential Offsetted Regression
Estimation for longitudinal data following outcome dependent sampling using the sequential offsetted regression technique. Includes support for binary, count, and continuous data. The first regression is a logistic regression, which uses a known ratio (the probability of being sampled given that the subject/observation was referred divided by the probability of being sampled given that the subject/observation was no referred) as an offset to estimate the probability of being referred given outcome and covariates. The second regression uses this estimated probability to calculate the mean population response given covariates.
Authors:
SOR_0.23.1.tar.gz
SOR_0.23.1.zip(r-4.5)SOR_0.23.1.zip(r-4.4)SOR_0.23.1.zip(r-4.3)
SOR_0.23.1.tgz(r-4.4-any)SOR_0.23.1.tgz(r-4.3-any)
SOR_0.23.1.tar.gz(r-4.5-noble)SOR_0.23.1.tar.gz(r-4.4-noble)
SOR_0.23.1.tgz(r-4.4-emscripten)SOR_0.23.1.tgz(r-4.3-emscripten)
SOR.pdf |SOR.html✨
SOR/json (API)
| # Install 'SOR' in R: |
| install.packages('SOR', repos = c('https://lsubioscomputing.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 7 years agofrom:831027827b. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 29 2024 |
| R-4.5-win | OK | Oct 29 2024 |
| R-4.5-linux | OK | Oct 29 2024 |
| R-4.4-win | OK | Oct 29 2024 |
| R-4.4-mac | OK | Oct 29 2024 |
| R-4.3-win | OK | Oct 29 2024 |
| R-4.3-mac | OK | Oct 29 2024 |
Exports:sor
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sequentially Offsetted Regression | SOR-package SOR sor |
