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Semiparametric Regression Modeling with Mixtures of Berkson and Classical Error, with Application to Fallout from the Nevada Test Site

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  • Bani Mallick
  • F. Owen Hoffman
  • Raymond J. Carroll

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  • Bani Mallick & F. Owen Hoffman & Raymond J. Carroll, 2002. "Semiparametric Regression Modeling with Mixtures of Berkson and Classical Error, with Application to Fallout from the Nevada Test Site," Biometrics, The International Biometric Society, vol. 58(1), pages 13-20, March.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:1:p:13-20
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00013.x
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    References listed on IDEAS

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    1. Daniel W. Schafer, 2001. "Semiparametric Maximum Likelihood for Measurement Error Model Regression," Biometrics, The International Biometric Society, vol. 57(1), pages 53-61, March.
    2. Raymond J. Carroll & Kathryn Roeder & Larry Wasserman, 1999. "Flexible Parametric Measurement Error Models," Biometrics, The International Biometric Society, vol. 55(1), pages 44-54, March.
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    Cited by:

    1. Yin, Zanhua & Gao, Wei & Tang, Man-Lai & Tian, Guo-Liang, 2013. "Estimation of nonparametric regression models with a mixture of Berkson and classical errors," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1151-1162.
    2. Kukush Alexander & Shklyar Sergiy & Masiuk Sergii & Likhtarov Illya & Kovgan Lina & Carroll Raymond J & Bouville Andre, 2011. "Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-30, February.
    3. Raymond J. Carroll & Aurore Delaigle & Peter Hall, 2007. "Non‐parametric regression estimation from data contaminated by a mixture of Berkson and classical errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 859-878, November.
    4. Duchwan Ryu & Erning Li & Bani K. Mallick, 2011. "Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements," Biometrics, The International Biometric Society, vol. 67(2), pages 454-466, June.
    5. Susanne M. Schennach, 2013. "Regressions with Berkson errors in covariates - A nonparametric approach," Papers 1308.2836, arXiv.org.
    6. Erica Ponzi & Paolo Vineis & Kian Fan Chung & Marta Blangiardo, 2020. "Accounting for measurement error to assess the effect of air pollution on omic signals," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-16, January.
    7. Cornelis J. Potgieter & Rubin Wei & Victor Kipnis & Laurence S. Freedman & Raymond J. Carroll, 2016. "Moment reconstruction and moment‐adjusted imputation when exposure is generated by a complex, nonlinear random effects modeling process," Biometrics, The International Biometric Society, vol. 72(4), pages 1369-1377, December.
    8. Raymond J. Carroll, 2003. "Variances Are Not Always Nuisance Parameters," Biometrics, The International Biometric Society, vol. 59(2), pages 211-220, June.
    9. 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.
    10. Jackson, Chris & Mosleh, Ali, 2016. "Bayesian inference with overlapping data: Reliability estimation of multi-state on-demand continuous life metric systems with uncertain evidence," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 124-135.

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