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Estimating the Cumulative incidence Functions under Length-biased Sampling [PDF]

, 2004
Consider a population of individuals who experience K dierent causes of death.We observe the ones alive at time t0 and follow them until death or possiblecensoring time. Given this length biased sample, we introduce estimators ofthe cumulative incidence functions of "initial survival times" (i.e.
Jean-Yves Dauxois, Agathe Guilloux
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Statistical inference methods for cumulative incidence function curves at a fixed point in time

Communications in Statistics Part B: Simulation and Computation, 2020
Yawen Hou, Zheng Chen
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Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

Ca-A Cancer Journal for Clinicians, 2021
, Ahmedin Jemal, Mathieu Laversanne
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A Flexible Parametric Competing-risks Model Using a Direct Likelihood Approach for the Cause-specific Cumulative Incidence Function

The Stata Journal, 2017
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Kaplan–Meier survival analysis overestimates cumulative incidence of health-related events in competing risk settings: a meta-analysis

Journal of Clinical Epidemiology, 2018
Peter Faris, Derek J Roberts, Todd Wilson   +2 more
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Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Ca-A Cancer Journal for Clinicians, 2018
, Ahmedin Jemal, Freddie Bray
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Multiple imputation methods for nonparametric inference on cumulative incidence with missing cause of failure

Statistics in Medicine, 2014
Minjung Lee
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Flexible parametric modelling of the cause‐specific cumulative incidence function

Statistics in Medicine, 2017
Michael Crowther, Paul Lambert, Sally R Wilkes   +2 more
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Cancer statistics for Asian Americans, Native Hawaiians, and Pacific Islanders, 2016: Converging incidence in males and females

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, Ahmedin Jemal, Moon Chen
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SAS macros for estimation of direct adjusted cumulative incidence curves under proportional subdistribution hazards models

Computer Methods and Programs in Biomedicine, 2011
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