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.

Version: 0.23.1
Depends: Matrix
Imports: methods, stats
Published: 2018-04-25
Author: Lee McDaniel [aut, cre], Jonathan Schildcrout [aut]
Maintainer: Lee McDaniel <lmcda4 at lsuhsc.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: SOR results

Documentation:

Reference manual: SOR.pdf

Downloads:

Package source: SOR_0.23.1.tar.gz
Windows binaries: r-devel: SOR_0.23.1.zip, r-release: SOR_0.23.1.zip, r-oldrel: SOR_0.23.1.zip
macOS binaries: r-release (arm64): SOR_0.23.1.tgz, r-oldrel (arm64): SOR_0.23.1.tgz, r-release (x86_64): SOR_0.23.1.tgz, r-oldrel (x86_64): SOR_0.23.1.tgz
Old sources: SOR archive

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