Goodness of fit in models for mortality data
Mortality data on an aggregate level are characterized by very large sample sizes. For this reason, uninformative outcomes are evident in common Goodness-of-Fit measures. In this paper we propose a new measure that allows comparison of different mortality models even for large sample sizes. Particularly, we develop a measure which uses a null model specifically designed for mortality data. Several simulation studies and actual applications will demonstrate the performances of this new measure with special emphasis on demographic models and Pspline approach.
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- Cameron, A Colin & Windmeijer, Frank A G, 1996.
"R-Squared Measures for Count Data Regression Models with Applications to Health-Care Utilization,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 14(2), pages 209-20, April.
- Cameron, A.C. & Windmeijer, F.A.G., 1993. "R-Squared Measures for Count Data Regression Models with Applications to Health Care Utilization," Papers 93-24, California Davis - Institute of Governmental Affairs.
- Veall, Michael R & Zimmermann, Klaus F, 1996. " Pseudo-R-[superscript 2] Measures for Some Common Limited Dependent Variable Models," Journal of Economic Surveys, Wiley Blackwell, vol. 10(3), pages 241-59, September.
- Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
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- repec:cup:cbooks:9780521785167 is not listed on IDEAS
- Mittlbock, M. & Waldhor, T., 2000. "Adjustments for R2-measures for Poisson regression models," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 461-472, October.
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