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:Lee McDaniel [aut, cre], Jonathan Schildcrout [aut]

SOR_0.23.1.tar.gz
SOR_0.23.1.zip(r-4.7)SOR_0.23.1.zip(r-4.6)SOR_0.23.1.zip(r-4.5)
SOR_0.23.1.tgz(r-4.6-any)SOR_0.23.1.tgz(r-4.5-any)
SOR_0.23.1.tar.gz(r-4.7-any)SOR_0.23.1.tar.gz(r-4.6-any)
SOR_0.23.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SOR/json (API)

# Install 'SOR' in R:
install.packages('SOR', repos = c('https://lsubioscomputing.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.

1.70 score 2 scripts 157 downloads 5 mentions 1 exports 2 dependencies

Last updated from:831027827b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK143
source / vignettesOK156
linux-release-x86_64OK124
macos-release-arm64OK89
macos-oldrel-arm64OK87
windows-develOK110
windows-releaseOK78
windows-oldrelOK95
wasm-releaseOK93

Exports:sor

Dependencies:latticeMatrix