IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v60y1997i2p277-292.html
   My bibliography  Save this article

Variable Selection for the Growth Curve Model

Author

Listed:
  • Satoh, Kenichi
  • Kobayashi, Mika
  • Fujikoshi, Yasunori

Abstract

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

Suggested Citation

  • Satoh, Kenichi & Kobayashi, Mika & Fujikoshi, Yasunori, 1997. "Variable Selection for the Growth Curve Model," Journal of Multivariate Analysis, Elsevier, vol. 60(2), pages 277-292, February.
  • Handle: RePEc:eee:jmvana:v:60:y:1997:i:2:p:277-292
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(96)91658-9
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:60:y:1997:i:2:p:277-292. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.