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Variable Selection for the Growth Curve Model


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  • Satoh, Kenichi
  • Kobayashi, Mika
  • Fujikoshi, Yasunori
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    In this paper we consider the problem of selecting the covariables within individuals in the growth curve model. We propose two modifications ofAICandMIC(Cp-static), which have improvements on the bias properties. Asymptotic distributions of variable slection criteria are derived under a general situation where a polynomial growth curve of degreej0is approximately suitable. A simulation study is also given to gain some understanding on the small sample properties of these variable selection criteria

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 60 (1997)
    Issue (Month): 2 (February)
    Pages: 277-292

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    Handle: RePEc:eee:jmvana:v:60:y:1997:i:2:p:277-292

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    Keywords: growth curve model variable selection AIC Cp-statistic MIC modifications of AIC and MIC;


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    Cited by:
    1. Hu, Jianhua & Xin, Xin & You, Jinhong, 2014. "Model determination and estimation for the growth curve model via group SCAD penalty," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 199-213.
    2. Siotani, Minoru & Wakaki, Hirofumi, 2006. "Contributions to multivariate analysis by Professor Yasunori Fujikoshi," Journal of Multivariate Analysis, Elsevier, vol. 97(9), pages 1914-1926, October.
    3. Fujikoshi, Yasunori & Enomoto, Rie & Sakurai, Tetsuro, 2013. "High-dimensional AIC in the growth curve model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 239-250.
    4. Soler, Julia M. P. & Singer, Julio M., 2000. "Optimal covariance adjustment in growth curve models," Computational Statistics & Data Analysis, Elsevier, vol. 33(1), pages 101-110, March.


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