On the incidence-prevalence relation and length-biased sampling

Canadian Journal of Statistics

Volumn 37, Issue 2, 2009, Pages 206-218

  Addona, Vittorio ^a   Asgharian, Masoud ^b   Wolfson, David B ^b  

^a MACALESTER COLLEGE   (United States)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Incidence rate; Left truncation; Nonparametric maximum likelihood estimator (npmle); Prevalent cohort; Right censoring

Indexed keywords

EID: 74049097223     PISSN: 03195724     EISSN: None     Source Type: Journal    
DOI: 10.1002/cjs.10011     Document Type: Article

References (32)

1. V. Addona & D. B. Wolfson (2006). A formal test for the stationarity of the incidence rate using data from a prevalent cohort study with follow-up. Lifetime Data Analysis, 12(3), 267-284.
2. A. Alioum, D. Commenges, R. Thiébaut & F. Dabis (2005). A multi-state approach for estimating the incidence of human immunodeficiency virus by using data from a prevalent cohort study. Applied Statistics, 54 (Part 4), 739-752.
3. M. Asgharian & D. B. Wolfson (2005). Asymptotic behaviour of the unconditional NPMLE of the length- biased survivor function from right censored prevalent cohort data. The Annals of Statistics, 33(5), 2109-2131.
4. M. Asgharian, C. E. M'Lan & D. B. Wolfson (2002). Length-biased sampling with right censoring: An unconditional approach. Journal of the American Statistical Association, 97(457), 201-209.
5. M. Asgharian, D. W. Wolfson & X. Zhang, (2006). Checking stationarity of the incidence rate using prevalent cohort survival data. Statistics in Medicine, 25, 1751-1767.
6. F. Biering-Sorensen & J. Hilden (1984). Reproducibility of the history of low-back trouble. Spine 9 (3), 280-286.
7. D. R. Cox (1969). Some sampling problems in technology. In New Developments in Survey Sampling, Johnson & Smith, editors. Wiley, New York, pp. 506-527.
8. M. Csorgo & Revesz (1981). Strong Approximation in Probability and Statistics. Academic Press, New York.
9. CSHA Working Group (1994). Canadian study of health and aging: study methods and prevalence of dementia. Journal of the Canadian Medical Association, 150, 899-913.
10. CSHA Working Group (2000). The incidence of dementia in Canada. Neurology, 55, 66-73.
11. I. D. Diamond & J. W. McDonald (1991). Analysis of current-status data. In Demographic Applications of Event History Analysis, Chapter 12, J. Trussell, R. Hankinson, & J. Tilton, editors. Oxford University Press, Oxford.
12. Z. Folnegovic & V. Folnegovic-Smalc (1992). Schizophrenia in Croatia: Interregional differences in preva- lence and a comment on constant incidence. Journal of Epidemiology and Community Health, 46, 248-255.
13. R. Hébert, J. Lindsay, R. Verreault, K. Rockwood, G. Hill & M-F Dubois (2000). Vascular dementia: Incidence and risk factors in the Canadian Study of Health and Aging. Stroke, 31, 1487-1493.
14. H. Guo (2006). Doubly censored prevalent cohort survival data. Unpublished Master's Thesis, Department of Mathematics and Statistics, McGill University, Montreal, Canada.
15. A. Jemal, T. Murray, E. Ward, A. Samuels, R. C. Tiwari, A. Ghafoor, E. J. Feuer & M. J. Thun (2005). Cancer Statistics, 2005. CA: A Cancer Journal for Clinicians, 55, 10-30.
16. N. Keiding (1991). Age-specific incidence and prevalence: A statistical perspective (withdiscussion). Journal of the Royal Statistical Society, Series A, 154 (3), 371-412.
17. N. Keiding (2006). Event history analysis and the cross-section. Statistics in Medicine, 25, 2343-2364.
18. N. Keiding, C. Holst & A. Green (1989). Retrospective estimation of diabetes incidence from information in a current prevalent population and historical mortality. American Journal of Epidemiology, 130, 588-600.
19. J. Neyman (1955). Statistics-Servant of all sciences. Science, 122(3166), 401-406.
20. Y. Ogata, K. Katsura, N. Keiding, C. Holst & A. Green (2000). Empirical Bayes age-period-cohort analysis of retrospective incidence data. Scandinavian Journal of Statistics, 27, 415-432.
21. G. P. Patil & C. R. Rao (1978). Weighted distributions and sized-biased sampling with applications to wildlife populations and human families. Biometrics, 34, 179-189.
22. K. J. Rothman & S. Greenland (2004). Concepts and methodological approaches in epidemiology. In The Handbook of Epidemiology, W. Ahrens & I. Pigeot, editors. Springer, New York.
23. E. J. Sorenson, A. P. Stalker, L. T. Kurland & A. J. Windebank (2002). Amyotrophic lateral sclerosis in Olmsted County, Minnesota, 1925 to 1998. Neurology, 59, 280-282.
24. N. Sourial (2003). Impact of uncertainty in onset time of disease on survival estimates. Unpublished Master's Thesis, Department of Mathematics and Statistics, McGill University, Montreal, Canada.
25. Statistics Canada (2006) Census of Population, Statistics Canada catalogue no. 97-551-XCB2006005: Age Groups and Sex for the Population of Canada, Provinces and Territories, 1921 to 2006 Censuses. Ottawa: Statistics Canada.
26. A. W. Van der Vaart (1998). Asymptotic Statistics. Cambridge Series in Statistics and Probabilistic Mathematics. Cambridge University Press, Cambridge, UK.
27. Y. Vardi (1982). Nonparametric estimation in the presence of length bias. The Annals of Statistics, 10, 616-620.
28. Y. Vardi (1985). Empirical distributions in selection bias models. The Annals of Statistics, 13, 178-205.
29. Y. Vardi (1989). Multiplicative censoring, renewal processes, deconvolution and decreasing density: non- parametric estimation. Biometrika, 76 (4), 751-761.
30. M-C. Wang (1991). Nonparametric estimation from cross-sectional survival data. Journal of the American Statistical Association, 86 (413), 130-143.
31. S. D. Wicksell (1925). The Corpuscle problem: A mathematical study of a biometric problem. Biometrika, 17(1) 84-99.
32. C. Wolfson, D. B. Wolfson, M. Asgharian, C. E. M'Lan, T. Østbye, K. Rockwood & D. B. Hogan (2001). A reevaluation of the duration of survival after the onset of dementia. New England Journal of Medicine, 344(15),1111-1116.