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A new test for the Box-Cox transformation model: An analysis of length of hospital stay for diabetes patients in Japan

Author

Listed:
  • Kazumitsu Nawata

    (University of Tokyo)

  • Koichi Kawabuchi

    (Tokyo Medical and Dental University)

Abstract

The Box-Cox (1964) transformation model (BC model) is widely used to examine various problems. The likelihood function under the normality assumption is misspecified, and the maximum likelihood estimator (BC MLE) cannot in general be consistent. However, under the “small sigma” assumption described in Bickel and Doksum (1981), the BC MLE can be consistent. It is, therefore, necessary to test whether this assumption is satisfied when the BC model is used. In this paper, we propose a new test of whether or not the BC MLE can be used based on the estimator proposed by Nawata (2013). We then analyze length of hospital stay for type 2 diabetes patients hospitalized for educational programs about managing diabetes at home. A dataset of 970 patients collected from 27 general hospitals in Japan is used.

Suggested Citation

  • Kazumitsu Nawata & Koichi Kawabuchi, 2014. "A new test for the Box-Cox transformation model: An analysis of length of hospital stay for diabetes patients in Japan," Economics Bulletin, AccessEcon, vol. 34(1), pages 324-332.
    • Handle: RePEc:ebl:ecbull:eb-13-00735
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    File URL: http://www.accessecon.com/Pubs/EB/2014/Volume34/EB-14-V34-I1-P32.pdf
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    References listed on IDEAS

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    1. Kazumitsu Nawata, 2013. "A new estimator of the Box-Cox transformation model using moment conditions," Economics Bulletin, AccessEcon, vol. 33(3), pages 2287-2297.
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    Cited by:

    1. Kazumitsu Nawata, 2015. "Robust estimation based on the third-moment restriction of the error terms for the Box-Cox transformation model: An estimator consistent under heteroscedasticity," Economics Bulletin, AccessEcon, vol. 35(2), pages 1056-1064.

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    1. Kazumitsu Nawata, 2015. "Robust estimation based on the third-moment restriction of the error terms for the Box-Cox transformation model: An estimator consistent under heteroscedasticity," Economics Bulletin, AccessEcon, vol. 35(2), pages 1056-1064.
    2. Nawata, Kazumitsu & McAleer, Michael, 2014. "The maximum number of parameters for the Hausman test when the estimators are from different sets of equations," Economics Letters, Elsevier, vol. 123(3), pages 291-294.

    More about this item

    Keywords

    Box-Cox transformation model; power transformation model; diabetes; length of stay (LOS);
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • I0 - Health, Education, and Welfare - - General

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