Semi-nonparametric estimation of regression-based survival models
AbstractTo 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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Bibliographic InfoArticle provided by AccessEcon in its journal Economics Bulletin.
Volume (Year): 3 (2007)
Issue (Month): 61 ()
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- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
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- Mark B. Stewart, 2004.
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"Testing the normality assumption in the sample selection model with an application to travel demand,"
00F37, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
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- Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
- 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.
- 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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