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Models for Intensive Longitudinal Data$
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Theodore A. Walls and Joseph L. Schafer

Print publication date: 2006

Print ISBN-13: 9780195173444

Published to Oxford Scholarship Online: March 2012

DOI: 10.1093/acprof:oso/9780195173444.001.0001

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Point Process Models for Event History Data: Applications in Behavioral Science

Point Process Models for Event History Data: Applications in Behavioral Science

Chapter:
(p.219) 10 Point Process Models for Event History Data: Applications in Behavioral Science
Source:
Models for Intensive Longitudinal Data
Author(s):

Stephen L. Rathbun

Saul Shiffman

Chad J. Gwaltney

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195173444.003.0010

This chapter discusses point process models for event history data. A point process is a stochastic mechanism for producing the times of the events of a point pattern. Point process models are closely linked to survival modes; the application of survival models to temporal points is permitted. Point processes are focused on the times of events as they may appear on a calendar, while survival models emphasize the durations of time between successive events. Point process modeling emphasizes the estimation of the event occurrences rate, expressed as numbers of events per unit time. Investigation of the event rates may give insight into the mechanisms pertaining to the behavior of interest.

Keywords:   point process, event history, stochastic mechanism, survival models, behavior

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