April 28th 2015
Faculty of Economic and Business Sciences | Salón de Grados
Prevalent Cohort Studies: Length-Biased Sampling with Right Censoring
2015/04/28 – 12:30 h | Masoud Asgharian, Department of Mathematics and Statistics – McGill University (Canada)
Abstract
Logistic or other constraints often preclude the possibility of conducting incident cohort studies. A feasible alternative in such cases is to conduct a cross-sectional prevalent cohort study for which we recruit prevalent cases, that is, subjects who have already experienced the initiating event, say the onset of a disease. When the interest lies in estimating the lifespan between the initiating event and a terminating event, say death for instance, such subjects may be followed prospectively until the terminating event or loss to follow-up, whichever happens first. It is well known that prevalent cases have, on average, longer lifespans. As such, they do not form a representative random sample from the target population; they comprise a biased sample. If the initiating events are generated from a stationary Poisson process, the so-called stationarity assumption, this bias is called length bias. I present the basics of nonparametric inference using length-biased right censored failure time data. I’ll then discuss some recent progress and current challenges. Our study is mainly motivated by challenges and questions raised in analyzing survival data collected on patients with dementia as part of a nationwide study in Canada, called the Canadian Study of Health and Aging (CSHA). I’ll use these data throughout the talk to discuss and motivate our methodology and its applications.
References:
A. Ertefaie, M. Asgharian and D. Stephens (2015). Double Bias. International Journal of Biostatistics. (available online)
M. Asgharian, C. Wolfson and D. B. Wolfson (2014). The Analysis of Biased Survival Data: The Canadian Study of Health and Aging and Beyond. Statistics in Action: A Canadian Outlook, pp 193-208. Edited by Jerry Lawless, CRC.
A. Ertefaie, M. Asgharian and D. Stephens (2014). The Propensity Score Estimation in the Presence of Length-bias Sampling: A Nonparametric Adjustment Approach. Stat, 3: 83-94.
M. Carone, M. Asgharian and N. Jewell (2014). Estimating the lifetime risk of dementia in the Canadian population using cross-sectional survival data. JASA, 109(505): 24-35.
J. Ning, J. Qin, M. Asgharian and Y. Shen (2013). Empirical likelihood-based confidence intervals for length-biased data. Stat. in Med., 32(13): 2278-2291.
M. Carone, M. Asgharian and M.-C. Wang (2012). Nonparametric Incidence Estimation From Prevalent Cohort Survival Data. Biometrika, V. 99(3): 599-613.
M. Asgharian, M. Carone and V. Fakoor (2012). Large Sample Study of the Kernel Density Estimates under Multiplicative Censoring. The Ann. Statist., 40(1): 159-187.
V. Addona, M. Asgharian, D. B.Wolfson (2009). On the incidence-prevalence relation and length-biased sampling. CJS, 37(2): 206-218.
P.-J. Bergeron, M. Asgharian, and D. B. Wolfson (2008). Covariate Bias Induced by Length-Biased Sampling of Failure Times. JASA, 103(482): 737-742.
M. Asgharian and David B. Wolfson, X. Zhang (2006). A Simple Criterion for the Stationarity of the Incidence Rate from Prevalent Cohort Studies. Stat. in Med., 25(10): 1751-1767.
M. Asgharian, David B. Wolfson (2005). Asymptotic Behaviour of the Unconditional NPMLE of the Length-Biased Survivor Function from Right Censored Prevalent Cohort Data. The Ann. Statist., 33(5): 2109-2131.
M. Asgharian (2003). Biased Sampling With Right Censoring: A Note on Sun, Cui, Tiwari(2002). CJS, 31(3): 349-350.
M. Asgharian and David B. Wolfson (2003). Some Issues Concerning Length-biased Sampling in Survival Analysis. Recent Advances and Trends in Nonparametric Statistics. Edited by M.G. Akritas and D.N. Politis, pp. 367-375.
M. Asgharian, C. E. M’Lan and David B. Wolfson (2002). Length-Biased Sampling With Right Censoring: An Unconditional Approach. JASA, 97(457): 201-209.
C. Wolfson, D. Wolfson, M. Asgharian, C. E. M’Lan, T. Østbye, K. Rockwood, D.B. Hogan (2001). A Re-Evaluation of the Duration of Survival after the Onset of Dementia. The New England Journal of Medicine, 344(15): 1111-1116.
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