Chapter

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

Stephen L. Rathbun, Saul Shiffman and Chad J. Gwaltney

in Models for Intensive Longitudinal Data

Published in print February 2006 | ISBN: 9780195173444
Published online March 2012 | e-ISBN: 9780199847051 | DOI: https://dx.doi.org/10.1093/acprof:oso/9780195173444.003.0010
Point Process Models for Event History Data: Applications in Behavioral Science

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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

Chapter.  13393 words.  Illustrated.

Subjects: Social Psychology

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