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Latent-model robustness in structural measurement error models

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  • Xianzheng Huang
  • Leonard A. Stefanski
  • Marie Davidian

Abstract

We present methods for diagnosing the effects of model misspecification of the true-predictor distribution in structural measurement error models. We first formulate latent-model robustness theoretically. Then we provide practical techniques for examining the adequacy of an assumed latent predictor model. The methods are illustrated via analytical examples, application to simulated data and with data from a study of coronary heart disease. Copyright 2006, Oxford University Press.

Suggested Citation

  • Xianzheng Huang & Leonard A. Stefanski & Marie Davidian, 2006. "Latent-model robustness in structural measurement error models," Biometrika, Biometrika Trust, vol. 93(1), pages 53-64, March.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:1:p:53-64
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    File URL: http://hdl.handle.net/10.1093/biomet/93.1.53
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    Cited by:

    1. Carroll, Raymond J. & Delaigle, Aurore & Hall, Peter, 2009. "Nonparametric Prediction in Measurement Error Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 993-1003.
    2. Raymond Carroll & Xiaohong Chen & Yingyao Hu, 2010. "Identification and estimation of nonlinear models using two samples with nonclassical measurement errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 379-399.
    3. Jaeun Choi & Donglin Zeng & Andrew F. Olshan & Jianwen Cai, 2018. "Joint modeling of survival time and longitudinal outcomes with flexible random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 126-152, January.
    4. Xianzheng Huang & Leonard A. Stefanski & Marie Davidian, 2009. "Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process," Biometrics, The International Biometric Society, vol. 65(3), pages 719-727, September.
    5. Xianzheng Huang & Joshua M. Tebbs, 2009. "On Latent-Variable Model Misspecification in Structural Measurement Error Models for Binary Response," Biometrics, The International Biometric Society, vol. 65(3), pages 710-718, September.
    6. Yehua Li & Annamaria Guolo & F. Owen Hoffman & Raymond J. Carroll, 2007. "Shared Uncertainty in Measurement Error Problems, with Application to Nevada Test Site Fallout Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1226-1236, December.
    7. BHATTI, M.Ishaq & BODLA, Mahmud, A., 2008. "Empirical Power Comparison Of Non-Nested Tests For The Evm: Some Monte Carlo Evidence," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 5(2).

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