Competing approaches to analysis of failure times with competing risks


Farley, TM; Ali, MM; Slaymaker, E; (2001) Competing approaches to analysis of failure times with competing risks. Statistics in medicine, 20 (23). pp. 3601-10. ISSN 0277-6715

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Abstract

: For the analysis of time to event data in contraceptive studies when individuals are subject to competing causes for discontinuation, some authors have recently advocated the use of the cumulative incidence rate as a more appropriate measure to summarize data than the complement of the Kaplan-Meier estimate of discontinuation. The former method estimates the rate of discontinuation in the presence of competing causes, while the latter is a hypothetical rate that would be observed if discontinuations for the other reasons could not occur. The difference between the two methods of analysis is the continuous time equivalent of a debate that took place in the contraceptive literature in the 1960s, when several authors advocated the use of net (adjusted or single decrement life table rates) rates in preference to crude rates (multiple decrement life table rates). A small simulation study illustrates the interpretation of the two types of estimate - the complement of the Kaplan-Meier estimate corresponds to a hypothetical rate where discontinuations for other reasons did not occur, while the cumulative incidence gives systematically lower estimates. The Kaplan-Meier estimates are more appropriate when estimating the effectiveness of a contraceptive method, but the cumulative incidence estimates are more appropriate when making programmatic decisions regarding contraceptive methods. Other areas of application, such as cancer studies, may prefer to use the cumulative incidence estimates, but their use should be determined according to the application.<br/>

Item Type: Article
Keywords: Proportional hazards model, Comparative Study, Computer Simulation, Contraception, methods, standards, Female, Human, Intrauterine Devices, standards, Life Tables, Pregnancy, Proportional Hazards Models, Randomized Controlled Trials, Statistics, methods, Support, Non-U.S. Gov't
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Population Health (2012- ) > Dept of Population Studies (1974-2012)
Faculty of Epidemiology and Population Health > Dept of Population Health (2012- )
Research Centre: Population Studies Group
PubMed ID: 11746340
Web of Science ID: 172447800010
URI: http://researchonline.lshtm.ac.uk/id/eprint/17495

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