A new class of minimum power divergence estimators with applications to cancer surveillance

Journal of Multivariate Analysis

Volumn 102, Issue 8, 2011, Pages 1175-1193

  Martín, Nirian ^a   Li, Yi ^b,c  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

62H17; 62J12; 62P10; Age adjusted cancer rates; Annual percent change (APC); Minimum power divergence estimators; Poisson sampling; Trends

Indexed keywords

EID: 79957635628     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2011.03.011     Document Type: Article

References (15)

1. Berkson J. Minimum chi-square, not maximum likelihood!. Annals of Statistics 1980, 8:457-487.
2. Bishop Y.M.M., Fienberg S.E., Holland P.W. Discrete Multivariate Analysis: Theory and Practice 1995, MIT Press, Cambridge.
3. Fay M., Tiwari R., Feuer E., Zou Z. Estimating average annual percent change for disease rates without assuming constant change. Biometrics 2006, 62:847-854.
4. M.J. Horner, L.A.G. Ries, M. Krapcho, N. Neyman, R. Aminou, N. Howlader, S.F. Altekruse, E.J. Feuer, L. Huang, A. Mariotto, B.A. Miller, D.R. Lewis, M.P. Eisner, D.G. Stinchcomb, B.K. Edwards (Eds), SEER Cancer Statistics Review, 1975-2006, National Cancer Institute, Bethesda, MD, http://seer.cancer.gov/csr/1975_2006/.
5. Imrey P.B. Power divergence methods. Encyclopedia of Biostatistics 2005, John Wiley and Sons, New York. P. Armitage, T. Colton (Eds.).
6. Kullback S., Leibler R.A. On information and sufficiency. The Annals of Mathematical Statistics 1951, 22:79-86.
7. Li Y., Tiwari R.C. Comparing trends in cancer rates across overlapping regions. Biometrics 2008, 64:1280-1286.
8. Li Y., Tiwari R.C., Zou Z. An age-stratified model for comparing trends in cancer rates across overlapping regions. Biometrical Journal 2008, 50:608-619.
9. Pardo L. Statistical Inference Based on Divergence Measures. Statistics: Textbooks and Monographs 2006, Chapman & Hall/CRC, New York.
10. Pardo L., Martín N. Homogeneity/heterogeneity hypotheses for standardized mortality ratios based on minimum power-divergence estimators. Biometrical Journal 2009, 51:819-836.
11. Pickle L.W., White A.A. Effects of the choice of age-adjustement method on maps of death rates. Statistics in Medicine 1995, 14:615-627.
12. Cressie N., Read T.R.C. Multinomial goodness-of-fit tests. Journal of the Royal Statistical Society B 1988, 46:440-464.
13. C. Riddell, J.M. Pliska, Cancer in Oregon, 2005: Annual Report on Cancer Incidence and Mortality among Oregonians. Department of Human Services, Oregon Public Health Division, Oregon State Cancer Registry, Portland, Oregon, 2008. http://egov.oregon.gov/DHS/ph/oscar/arpt2005/ar2005.pdf.
14. Tiwari R.C., Clegg L., Zou Z. Efficient interval estimation for age-adjusted cancer rates. Statistical Methods in Medical Research 2006, 15:547-569.
15. Walters K.A., Li Y., Tiwari R.C., Zou Z. A weighted-least-squares estimation approach to comparing trends in age-adjusted cancer rates across overlapping regions. Journal of Data Science 2010, 8:631-644.