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Binary response models with M-phase case-control data

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  • Chiang, Chin-Tsang
  • Huang, Ming-Yueh
  • Bai, Ren-Hong

Abstract

In this study, a more general single-index regression model was presented to characterize the relationship between a dichotomous response and covariates of interest. With M-phase (M≥2) case-control data supplemented by information on a response and certain covariates, we propose a pseudo maximum likelihood estimation for the index coefficients. In the receiver operating characteristic curve analysis, an estimation for the accuracy measure is further provided and is borrowed to seek an optimal linear predictor. As for the hypothesis of model correctness, a pseudo least squares approach is employed as an aid to devising suitable testing procedures. Moreover, the general theoretical frameworks of these estimators are well developed. Finally, extensive simulations and two empirical applications are used to illustrate the applicability of our methodology.

Suggested Citation

  • Chiang, Chin-Tsang & Huang, Ming-Yueh & Bai, Ren-Hong, 2013. "Binary response models with M-phase case-control data," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 332-348.
    • Handle: RePEc:eee:jmvana:v:116:y:2013:i:c:p:332-348
    DOI: 10.1016/j.jmva.2013.01.002
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    References listed on IDEAS

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    4. Nilanjan Chatterjee & Yi‐Hau Chen, 2007. "Maximum likelihood inference on a mixed conditionally and marginally specified regression model for genetic epidemiologic studies with two‐phase sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 123-142, April.
    5. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
    6. A. J. Lee & A. J. Scott & C. J. Wild, 2010. "Efficient estimation in multi-phase case-control studies," Biometrika, Biometrika Trust, vol. 97(2), pages 361-374.
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