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 |

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
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.