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A Semiparametric Odds Ratio Model for Measuring Association

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  • Hua Yun Chen

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  • Hua Yun Chen, 2007. "A Semiparametric Odds Ratio Model for Measuring Association," Biometrics, The International Biometric Society, vol. 63(2), pages 413-421, June.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:2:p:413-421
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00701.x
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    References listed on IDEAS

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    1. Hua Yun Chen, 2003. "A note on the prospective analysis of outcome‐dependent samples," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 575-584, May.
    2. Hua Yun Chen, 2004. "Nonparametric and Semiparametric Models for Missing Covariates in Parametric Regression," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1176-1189, December.
    3. Glen A. Satten & Raymond J. Carroll, 2000. "Conditional and Unconditional Categorical Regression Models with Missing Covariates," Biometrics, The International Biometric Society, vol. 56(2), pages 384-388, June.
    4. Kung‐Yee Liang & Jing Qin, 2000. "Regression analysis under non‐standard situations: a pairwise pseudolikelihood approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 773-786.
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    Citations

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    Cited by:

    1. Yi Qian & Hui Xie, 2013. "Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases," NBER Working Papers 19586, National Bureau of Economic Research, Inc.
    2. Yi Qian & Hui Xie, 2022. "Simplifying Bias Correction for Selective Sampling: A Unified Distribution-Free Approach to Handling Endogenously Selected Samples," Marketing Science, INFORMS, vol. 41(2), pages 336-360, March.
    3. Hua Yun Chen & Hui Xie & Yi Qian, 2011. "Multiple Imputation for Missing Values through Conditional Semiparametric Odds Ratio Models," Biometrics, The International Biometric Society, vol. 67(3), pages 799-809, September.
    4. Sung Jae Jun & Sokbae Lee, 2024. "Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 998-1009, July.
    5. Yilin Li & Wang Miao & Ilya Shpitser & Eric J. Tchetgen Tchetgen, 2023. "A self‐censoring model for multivariate nonignorable nonmonotone missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3203-3214, December.
    6. Chen, Hua Yun, 2010. "Compatibility of conditionally specified models," Statistics & Probability Letters, Elsevier, vol. 80(7-8), pages 670-677, April.
    7. Anders Skrondal & Sophia Rabe-Hesketh, 2022. "The Role of Conditional Likelihoods in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 799-834, September.
    8. Chen, Ziqi & Shi, Ning-Zhong & Gao, Wei, 2011. "Nonparametric estimation of the log odds ratio for sparse data by kernel smoothing," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1802-1807.
    9. Amanda Coston & Edward H. Kennedy, 2022. "The role of the geometric mean in case-control studies," Papers 2207.09016, arXiv.org.
    10. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Yi Qian & Hui Xie, 2015. "Drive More Effective Data-Based Innovations: Enhancing the Utility of Secure Databases," Management Science, INFORMS, vol. 61(3), pages 520-541, March.
    12. Tan, Zhiqiang, 2019. "On doubly robust estimation for logistic partially linear models," Statistics & Probability Letters, Elsevier, vol. 155(C), pages 1-1.
    13. Zhonghua Liu & Ting Ye & Baoluo Sun & Mary Schooling & Eric Tchetgen Tchetgen, 2023. "Mendelian randomization mixed‐scale treatment effect robust identification and estimation for causal inference," Biometrics, The International Biometric Society, vol. 79(3), pages 2208-2219, September.
    14. Eric J. Tchetgen Tchetgen & James Robins, 2010. "The Semiparametric Case-Only Estimator," Biometrics, The International Biometric Society, vol. 66(4), pages 1138-1144, December.

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