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Nonparametric Varying-Coefficient Models for the Analysis of Longitudinal Data

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  • Colin O. Wu
  • Kai F. Yu

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  • Colin O. Wu & Kai F. Yu, 2002. "Nonparametric Varying-Coefficient Models for the Analysis of Longitudinal Data," International Statistical Review, International Statistical Institute, vol. 70(3), pages 373-393, December.
    • Handle: RePEc:bla:istatr:v:70:y:2002:i:3:p:373-393
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    File URL: http://hdl.handle.net/10.1111/j.1751-5823.2002.tb00176.x
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    References listed on IDEAS

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    1. Ludwig Fahrmeir & Stefan Lang, 2001. "Bayesian inference for generalized additive mixed models based on Markov random field priors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(2), pages 201-220.
    2. Hall, Peter & Titterington, D. M., 1988. "On confidence bands in nonparametric density estimation and regression," Journal of Multivariate Analysis, Elsevier, vol. 27(1), pages 228-254, October.
    3. John A. Rice & Colin O. Wu, 2001. "Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves," Biometrics, The International Biometric Society, vol. 57(1), pages 253-259, March.
    4. Colin Wu & Kai Yu & Chin-Tsang Chiang, 2000. "A Two-Step Smoothing Method for Varying-Coefficient Models with Repeated Measurements," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(3), pages 519-543, September.
    5. Jianhua Z. Huang, 2002. "Varying-coefficient models and basis function approximations for the analysis of repeated measurements," Biometrika, Biometrika Trust, vol. 89(1), pages 111-128, March.
    6. Hart, Jeffrey D. & Wehrly, Thomas E., 1993. "Consistency of cross-validation when the data are curves," Stochastic Processes and their Applications, Elsevier, vol. 45(2), pages 351-361, April.
    7. Geert Verbeke & Geert Molenberghs & Herbert Thijs & Emmanuel Lesaffre & Michael G. Kenward, 2001. "Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach," Biometrics, The International Biometric Society, vol. 57(1), pages 7-14, March.
    8. Besse, Philippe C. & Cardot, Herve & Ferraty, Frederic, 1997. "Simultaneous non-parametric regressions of unbalanced longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 24(3), pages 255-270, May.
    9. Göran Kauermann, 2000. "Modeling Longitudinal Data with Ordinal Response by Varying Coefficients," Biometrics, The International Biometric Society, vol. 56(3), pages 692-698, September.
    10. X. Lin & D. Zhang, 1999. "Inference in generalized additive mixed modelsby using smoothing splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 381-400, April.
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    Cited by:

    1. Lee, Kyeongeun & Lee, Young K. & Park, Byeong U. & Yang, Seong J., 2018. "Time-dynamic varying coefficient models for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 50-65.
    2. Senturk, Damla & Nguyen, Danh V., 2006. "Estimation in covariate-adjusted regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3294-3310, July.
    3. Hans-Georg Müller & Ying Zhang, 2005. "Time-Varying Functional Regression for Predicting Remaining Lifetime Distributions from Longitudinal Trajectories," Biometrics, The International Biometric Society, vol. 61(4), pages 1064-1075, December.
    4. Byeong U. Park & Enno Mammen & Young K. Lee & Eun Ryung Lee, 2015. "Varying Coefficient Regression Models: A Review and New Developments," International Statistical Review, International Statistical Institute, vol. 83(1), pages 36-64, April.
    5. Lee Myoung-jae, 2015. "Panel conditional and multinomial logit with time-varying parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(3), pages 317-337, June.

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