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Regression analysis with censored data: Extensions of Koul-Susarla-Van Ryzin approach

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  • Zhou, Mai

Abstract

Koul et al. (1981, Ann. Statist. 9, 1276-1288) proposed a new method of inference in regression models with randomly right censored data and showed that the estimator it produces is consistent and asymptotically normally distributed. This paper reviews the many extensions and modifications of this method that have appeared since. To further advance the method, we propose to study an extension of the residuals in such models with censored data. The usefulness of the residual analysis in model diagnostics is demonstrated by two examples.

Suggested Citation

  • Zhou, Mai, 1999. "Regression analysis with censored data: Extensions of Koul-Susarla-Van Ryzin approach," Statistics & Probability Letters, Elsevier, vol. 41(3), pages 229-236, February.
  • Handle: RePEc:eee:stapro:v:41:y:1999:i:3:p:229-236
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    References listed on IDEAS

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    1. Lai, T. L. & Ying, Z. L. & Zheng, Z. K., 1995. "Asymptotic Normality of a Class of Adaptive Statistics with Applications to Synthetic Data Methods for Censored Regression," Journal of Multivariate Analysis, Elsevier, vol. 52(2), pages 259-279, February.
    2. Fygenson, Mendel & Zhou, Mai, 1992. "Modifying the Koul, Susarla and Van Ryzin estimator for linear regression models with right censoring," Statistics & Probability Letters, Elsevier, vol. 13(4), pages 295-299, March.
    3. Srinivasan, C. & Zhou, M., 1994. "Linear Regression with Censoring," Journal of Multivariate Analysis, Elsevier, vol. 49(2), pages 179-201, May.
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    Cited by:

    1. Satten, Glen A. & Datta, Somnath & Robins, James, 2001. "Estimating the marginal survival function in the presence of time dependent covariates," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 397-403, October.

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