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Estimation in a semiparametric model for longitudinal data with unspecified dependence structure

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  • Xuming He

Abstract

This paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large-sample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases are the analysis of the conditional mean and median functions for longitudinal data. Copyright Biometrika Trust 2002, Oxford University Press.

Suggested Citation

  • Xuming He, 2002. "Estimation in a semiparametric model for longitudinal data with unspecified dependence structure," Biometrika, Biometrika Trust, vol. 89(3), pages 579-590, August.
  • Handle: RePEc:oup:biomet:v:89:y:2002:i:3:p:579-590
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