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Rank regression for current-status data: asymptotic normality

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  • Abrevaya, Jason

Abstract

A rank estimator proposed by Aragón and Quiróz (1995) for the linear regression model with current-status data is shown to be -consistent and asymptotically normal. Monte Carlo simulations investigate the performance of the estimator and the proposed covariance matrix estimator.

Suggested Citation

  • Abrevaya, Jason, 1999. "Rank regression for current-status data: asymptotic normality," Statistics & Probability Letters, Elsevier, vol. 43(3), pages 275-287, July.
    • Handle: RePEc:eee:stapro:v:43:y:1999:i:3:p:275-287
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    References listed on IDEAS

    as
    1. Aragón, Jorge & Quiróz, Adolfo J., 1995. "Rank regression for current status data," Statistics & Probability Letters, Elsevier, vol. 24(3), pages 251-256, August.
    2. Chamberlain, Gary, 1986. "Asymptotic efficiency in semi-parametric models with censoring," Journal of Econometrics, Elsevier, vol. 32(2), pages 189-218, July.
    3. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
    4. Cosslett, Stephen R, 1987. "Efficiency Bounds for Distribution-free Estimators of the Binary," Econometrica, Econometric Society, vol. 55(3), pages 559-585, May.
    5. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
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    Cited by:

    1. Shuangge Ma & Jian Huang, 2007. "Combining Multiple Markers for Classification Using ROC," Biometrics, The International Biometric Society, vol. 63(3), pages 751-757, September.
    2. Toshio Honda, 2004. "Nonparametric regression with current status data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(1), pages 49-72, March.
    3. Abrevaya, Jason, 1999. "Leapfrog estimation of a fixed-effects model with unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 93(2), pages 203-228, December.
    4. Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.

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