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Local EM Estimation of the Hazard Function for Interval-Censored Data

Author

Listed:
  • Rebecca A. Betensky
  • Jane C. Lindsey
  • Louise M. Ryan
  • M. P. Wand

Abstract

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Suggested Citation

  • Rebecca A. Betensky & Jane C. Lindsey & Louise M. Ryan & M. P. Wand, 1999. "Local EM Estimation of the Hazard Function for Interval-Censored Data," Biometrics, The International Biometric Society, vol. 55(1), pages 238-245, March.
  • Handle: RePEc:bla:biomet:v:55:y:1999:i:1:p:238-245
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.1999.00238.x
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    Citations

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    Cited by:

    1. Peter Hall & Terence Tao, 2002. "Relative efficiencies of kernel and local likelihood density estimators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 537-547, August.
    2. Richard J. Cook & Leilei Zeng & Ker-Ai Lee, 2008. "A Multistate Model for Bivariate Interval-Censored Failure Time Data," Biometrics, The International Biometric Society, vol. 64(4), pages 1100-1109, December.
    3. Peter Bacchetti & Christopher Quale, 2002. "Generalized Additive Models with Interval-Censored Data and Time-Varying Covariates: Application to Human Immunodeficiency Virus Infection in Hemophiliacs," Biometrics, The International Biometric Society, vol. 58(2), pages 443-447, June.
    4. Tianxi Cai & Rebecca A. Betensky, 2003. "Hazard Regression for Interval-Censored Data with Penalized Spline," Biometrics, The International Biometric Society, vol. 59(3), pages 570-579, September.
    5. Cai, T. & Hyndman, R.J. & Wand, M.P., 2000. "Mixed Model-Based Hazard Estimation," Monash Econometrics and Business Statistics Working Papers 11/00, Monash University, Department of Econometrics and Business Statistics.
    6. Els Goetghebeur & Louise Ryan, 2000. "Semiparametric Regression Analysis of Interval-Censored Data," Biometrics, The International Biometric Society, vol. 56(4), pages 1139-1144, December.
    7. Shu Jiang & Richard J. Cook, 2020. "A Mixture Model for Bivariate Interval-Censored Failure Times with Dependent Susceptibility," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 37-62, April.

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