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Linear regression with a randomly censored covariate: application to an Alzheimer's study

Author

Listed:
  • Folefac D. Atem
  • Jing Qian
  • Jacqueline E. Maye
  • Keith A. Johnson
  • Rebecca A. Betensky

Abstract

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Suggested Citation

  • Folefac D. Atem & Jing Qian & Jacqueline E. Maye & Keith A. Johnson & Rebecca A. Betensky, 2017. "Linear regression with a randomly censored covariate: application to an Alzheimer's study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 313-328, February.
    • Handle: RePEc:bla:jorssc:v:66:y:2017:i:2:p:313-328
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    References listed on IDEAS

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    1. Huixia Judy Wang & Xingdong Feng, 2012. "Multiple Imputation for M -Regression With Censored Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 194-204, March.
    2. Rigobon, Roberto & Stoker, Thomas M., 2009. "Bias From Censored Regressors," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 340-353.
    3. Shengchun Kong & Bin Nan, 2016. "Semiparametric approach to regression with a covariate subject to a detection limit," Biometrika, Biometrika Trust, vol. 103(1), pages 161-174.
    4. Roberto Rigobon & Thomas M. Stoker, 2007. "Estimation With Censored Regressors: Basic Issues," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1441-1467, November.
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