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Applied Longitudinal Data AnalysisModeling Change and Event Occurrence$
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Judith D. Singer and John B. Willett

Print publication date: 2003

Print ISBN-13: 9780195152968

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780195152968.001.0001

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Describing Continuous-Time Event Occurrence Data

Describing Continuous-Time Event Occurrence Data

Chapter:
(p.468) 13 Describing Continuous-Time Event Occurrence Data
Source:
Applied Longitudinal Data Analysis
Author(s):

Judith D. Singer

John B. Willett

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195152968.003.0013

This chapter presents strategies for describing continuous time event data. Section 13.1 identifies salient properties of continuous-time data and redefines the survivor and hazard functions as required. Section 13.2 estimates these functions using a pair of simple strategies—called the discrete-time and actuarial methods—that require the continuous event times to be grouped into intervals. Section 13.3 introduces a superior approach—the Kaplan–Meier method—that does not require the artificial grouping of data but that yields estimates of only the survivor, not the hazard, function. The remainder of the chapter offers solutions to the core conundrum embedded in continuous-time event data: the inability to estimate the hazard function well.

Keywords:   continuous-time data, survivor functions, hazard functions, Kaplan–Meier method

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