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A Double Varying-coefficient Modeling Approach for Analyzing Longitudinal Observations

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Abstract

The identification of within-subject dependence is important for constructing efficient estimation in longitudinal data models. In this paper, we proposed a flexible way to study this dependence by using nonparametric regression models. Specifically, we considered the estimation of varying coefficient longitudinal data model with non-stationary varying coefficient autoregressive error process over observational time quantum. Based on spline approximation and local polynomial techniques, we proposed a two-stage nonparametric estimation for unknown functional coefficients and didn’t not drop any observations in a hybrid least square loss framework. Moreover, we showed that the estimated coefficient functions are asymptotically normal and derived the asymptotic biases and variances accordingly. Monte Carlo studies and two real applications were conducted for illustrating the performance of our proposed methods.

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Author information

Authors and Affiliations

  1. School of Business, Ningbo University, Ningbo, 315211, China

    Qun-fang Xu

  2. School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, 201620, China

    Rui Li

  3. Key Laboratory of Advanced Theory and Application in Statistics and Data Science, East China Normal University, Ministry of Education, Shanghai, 200062, China

    Rui Li

Authors
  1. Qun-fang Xu
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  2. Rui Li
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Corresponding author

Correspondence to Rui Li.

Additional information

Xu’s research is supported by MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No.15YJA910004) and Sponsored by K.C. Wong Magna Fund in Ningbo University.

Li’s research is supported by the National Social Science Foundation of China (No.17BTJ025) and the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science (East China Normal University), Ministry of Education (No. KLATASDS1802).

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Xu, Qf., Li, R. A Double Varying-coefficient Modeling Approach for Analyzing Longitudinal Observations. Acta Math. Appl. Sin. Engl. Ser. 35, 671–688 (2019). https://doi.org/10.1007/s10255-019-0840-8

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  • DOI: https://doi.org/10.1007/s10255-019-0840-8

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