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Efficient logistic regression designs under an imperfect population identifier

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  • Paul S. Albert
  • Aiyi Liu
  • Tonja Nansel

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  • Paul S. Albert & Aiyi Liu & Tonja Nansel, 2014. "Efficient logistic regression designs under an imperfect population identifier," Biometrics, The International Biometric Society, vol. 70(1), pages 175-184, March.
    • Handle: RePEc:bla:biomet:v:70:y:2014:i:1:p:175-184
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    File URL: http://hdl.handle.net/10.1111/biom.12106
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    References listed on IDEAS

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    1. Mary J. Morrissey & Donna Spiegelman, 1999. "Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons," Biometrics, The International Biometric Society, vol. 55(2), pages 338-344, June.
    2. Helmut Küchenhoff & Samuel M. Mwalili & Emmanuel Lesaffre, 2006. "A General Method for Dealing with Misclassification in Regression: The Misclassification SIMEX," Biometrics, The International Biometric Society, vol. 62(1), pages 85-96, March.
    3. Rose Sherri & van der Laan Mark J., 2011. "A Targeted Maximum Likelihood Estimator for Two-Stage Designs," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-21, March.
    4. Todd A. Alonzo & Margaret Sullivan Pepe, 2005. "Assessing accuracy of a continuous screening test in the presence of verification bias," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(1), pages 173-190, January.
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    Cited by:

    1. Peizhou Liao & Hao Wu & Tianwei Yu, 2017. "ROC Curve Analysis in the Presence of Imperfect Reference Standards," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 91-104, June.

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