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Efficient Inference about the Partially Linear Varying Coefficient Model with Random Effect for Longitudinal Data

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Information Computing and Applications (ICICA 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 391))

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Abstract

This article considers the estimation for the partially linear varying coefficient model with random effect. This article proposes to use the estimators for the variance component and profile weighted semi-parametric least squares (WSLSE) techniques to estimate the parametric component efficiently and to establish its efficiency and asymptotic properties. The proposed estimator is proved to be more efficient than that naïve estimation with working independence error structure. Some Monte Carlo simulations are conducted to examine the finite sample performance. Moreover, from the empirical study, the newly proposed procedure performs well in moderate-sized samples.

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References

  1. Su, L., Ullah, A.: More efficient estimation of nonparametric panel data models with random effects. Economics Letters 96, 375–380 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  2. Huang, J.Z., Wu, C.O., Zhou, L.: Varying-Coefficient Models and Basis Function Approximations for the Analysis of Repeated Measurements. Biometrika 89, 111–128 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  3. Zhao, P.X., Xue, L.G.: Variable Selection for Semiparametric Varying Coefficient Partially Linear Errors-in-variable Models. J. Multivariate Anal. 101, 1872–1883 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  4. Hastie, T., Tibshirani, R.: Varying Coefficient Models. J. Roy. Statist. Soc. Ser. B 55, 757–796 (1993)

    MathSciNet  MATH  Google Scholar 

  5. Ahmad, I., Leelahanon, S., Li, Q.: Efficient. Estimation of a Semiparametric Partially Linear Varying Coefficient Model. The Annals of Statistics 33, 258–283 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  6. Fan, J., Huang, T.: Profile Likelihood Inferences on Semiparametric Varying Coefficient Partially Linear Models. Bernoulli 11, 1031–1057 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chiang, C.T., Rice, J.A., Wu, O.C.: Smoothing Spine Estimation for Varying Coefficient Models with Repeatedly Measured Dependent Variables. J. Am. Statist. Assoc. 96, 454 (2001)

    Article  MATH  Google Scholar 

  8. You, J., Zhou, X.: Partially Linear Models and Polynomial Spline Approximations for the Analysis of Unbalanced Panel Data. J. Stat. Plan Infer. 139, 679–695 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  9. Pang, Z., Xue, L.G.: Estimation for the Single-Index Models with Random Effects. Comput. Stat. Data An. 56, 1837–1853 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  10. de Boor, C.: A Practical Guide to Spines. Springer, New York (1978)

    Book  MATH  Google Scholar 

  11. Bickel, P.J., Klaassen, C.A., Ritov, Y., Wellner, J.A.: Efficient and Adaptive Estimation for Semi-parametric Models. Johns Hopkins, Series in the Mathematical Science. Johns Hopkins University Press, Baltimore (1993)

    MATH  Google Scholar 

  12. Kaslow, R.A., Ostrow, D.G., Detels, R., Phair, J.P., Polk, B.F., Rinaldo, C.R.: The multicenter AIDS cohort study: Rationale, organization and selected characteristics of the participants. American Journal of Epidemiology 126, 310–318 (1987)

    Article  Google Scholar 

  13. Fan, J., Huang, T., Li, R.: Analysis of longitudinal data with semi-parametric estimation of covariance function. J. Amer. Statist. Assoc. 102, 632–641 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  14. Qu, A., Li, R.: Quadratic inference functions for varying coefficient models with longitudinal data. Biometrics 62, 379–391 (2006)

    Article  MathSciNet  MATH  Google Scholar 

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Li, W., Xue, L. (2013). Efficient Inference about the Partially Linear Varying Coefficient Model with Random Effect for Longitudinal Data. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_56

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  • DOI: https://doi.org/10.1007/978-3-642-53932-9_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53931-2

  • Online ISBN: 978-3-642-53932-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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