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 |

Reference manual: | SOR.pdf |

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-release (x86_64): SOR_0.23.1.tgz, r-oldrel: SOR_0.23.1.tgz |

Old sources: | SOR archive |

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