SOR: Estimation using Sequential Offsetted Regression

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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.

Author
Lee McDaniel [aut, cre], Jonathan Schildcrout [aut]
Date of publication
2016-12-09 22:56:23
Maintainer
Lee McDaniel <lmcda4@lsuhsc.edu>
License
GPL-3
Version
0.23.0

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Man pages

sor
Sequentially Offsetted Regression

Files in this package

SOR
SOR/NAMESPACE
SOR/R
SOR/R/sor.R
SOR/R/normSOR.R
SOR/R/poisSOR.R
SOR/R/geemR.R
SOR/R/common.R
SOR/R/binomSOR.R
SOR/MD5
SOR/DESCRIPTION
SOR/man
SOR/man/sor.Rd