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Information and asymptotic efficiency of the case-cohort sampling design in Cox's regression model

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  • Zhang, Haimeng
  • Goldstein, Larry

Abstract

Efficiencies of the maximum pseudolikelihood estimator and a number of related estimators for the case-cohort sampling design in the proportional hazards regression model are studied. The asymptotic information and lower bound for estimating the parametric regression parameter are calculated based on the effective score, which is obtained by determining the component of the parametric score orthogonal to the space generated by the infinite-dimensional nuisance parameter. The asymptotic distributions of the maximum pseudolikelihood and related estimators in an i.i.d. setting show that these estimators do not achieve the computed asymptotic lower bound. Simple guidelines are provided to determine in which instances such estimators are close enough to efficient for practical purposes.

Suggested Citation

  • Zhang, Haimeng & Goldstein, Larry, 2003. "Information and asymptotic efficiency of the case-cohort sampling design in Cox's regression model," Journal of Multivariate Analysis, Elsevier, vol. 85(2), pages 292-317, May.
    • Handle: RePEc:eee:jmvana:v:85:y:2003:i:2:p:292-317
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    References listed on IDEAS

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    1. Greenwood, P. E. & Wefelmeyer, W., 1990. "Efficiency of estimators for partially specified filtered models," Stochastic Processes and their Applications, Elsevier, vol. 36(2), pages 353-370, December.
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    Cited by:

    1. Erik T. Parner & Per K. Andersen & Morten Overgaard, 2020. "Cumulative risk regression in case–cohort studies using pseudo-observations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 639-658, October.

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