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Survival Analysis$
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Shenyang Guo

Print publication date: 2009

Print ISBN-13: 9780195337518

Published to Oxford Scholarship Online: January 2010

DOI: 10.1093/acprof:oso/9780195337518.001.0001

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The Discrete-Time Models

The Discrete-Time Models

Chapter:
(p.56) 3 The Discrete-Time Models
Source:
Survival Analysis
Author(s):

Guo Shenyang

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195337518.003.0003

This chapter reviews the first type of multivariate model analyzing time-to-event data: the discrete-time models. The primary feature of this type of model is its approximation of hazard rate by using probability estimated from a person-time data set. When the study focuses on a single event, the analyst uses a binary logistic regression to estimate the probability. When the study focuses on multiple events (i.e., termination of study time due to more than one reason), the analyst uses a multinomial logit regression to estimate multiple probabilities. The discrete-time model of multiple events is also known as competing-risks analysis. The chapter begins with an overview of the discrete-time models. It then describes data conversion and the binary logistic regression for analyzing a single event. Finally, it reviews issues related to data conversion and the multinomial logit model for analyzing multiple events.

Keywords:   multivariate model analysis, time-to-event data, discrete-time models, binary logistic regression, multinomial logit regression

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