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Semi-nonparametric estimation of regression-based survival models

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  • Hiroaki Masuhara

    ()
    (Section of Health Economics, Department of Gerontological Policy, National Center for Geriatrics and Gerontology (NCGG))

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    Abstract

    To estimate survival data with unobserved heterogeneity, this paper proposes the generalized lognormal survival analysis using Hermite polynomials and the Box-Cox transformation. The General Social Survey (GSS) in 2002 demonstrates good performance of the proposed model.

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    File URL: http://www.accessecon.com/pubs/EB/2007/Volume3/EB-07C20101A.pdf
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    Bibliographic Info

    Article provided by AccessEcon in its journal Economics Bulletin.

    Volume (Year): 3 (2007)
    Issue (Month): 61 ()
    Pages: 1-12

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    Handle: RePEc:ebl:ecbull:eb-07c20101

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    1. Mark Stewart, 2002. "Semi-nonparametric estimation of extended ordered probit models," United Kingdom Stata Users' Group Meetings 2003 04, Stata Users Group.
    2. van der Klaauw, Bas & Koning, Ruud H, 2003. "Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 31-42, January.
    3. Gabler, Siegfried & Laisney, Francois & Lechner, Michael, 1993. "Seminonparametric Estimation of Binary-Choice Models with an Application to Labor-Force Participation," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 61-80, January.
    4. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
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    Cited by:
    1. Masuhara, Hiroaki, 2013. "Semiparametric duration analysis with an endogenous binary variable: An application to hospital stays," CIS Discussion paper series 597, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.

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