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Fitting binary regression models with case-augmented samples

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  • A. J. Lee
  • A. J. Scott
  • C. J. Wild
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    Abstract

    In a case-augmented study, measurements on a random sample from a population are augmented by information from an independent sample of cases, that is units with some characteristic of interest. We show that inferences about the effect of the covariates on the probability of being a case can be made by fitting a modified prospective likelihood. We also show that this procedure is fully efficient. Copyright 2006, Oxford University Press.

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    File URL: http://hdl.handle.net/10.1093/biomet/93.2.385
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    Bibliographic Info

    Article provided by Biometrika Trust in its journal Biometrika.

    Volume (Year): 93 (2006)
    Issue (Month): 2 (June)
    Pages: 385-397

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    Handle: RePEc:oup:biomet:v:93:y:2006:i:2:p:385-397

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    Cited by:
    1. Alan Lee & Yuichi Hirose, 2010. "Semi-parametric efficiency bounds for regression models under response-selective sampling: the profile likelihood approach," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(6), pages 1023-1052, December.

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