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Dynamic Analysis of Recurrent Event Data Using the Additive Hazard Model
Author(s) -
Fosen Johan,
Borgan Ørnulf,
WeedonFekjær Harald,
Aalen Odd O.
Publication year - 2006
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200510217
Subject(s) - covariate , proportional hazards model , event (particle physics) , statistics , econometrics , event data , computer science , data set , regression analysis , mathematics , data mining , physics , quantum mechanics
We propose a method for analysis of recurrent event data using information on previous occurrences of the event as a time‐dependent covariate. The focus is on understanding how to analyze the effect of such a dynamic covariate while at the same time ensuring that the effects of treatment and other fixed covariates are unbiasedly estimated. By applying an additive regression model for the intensity of the recurrent events, concepts like direct, indirect and total effects of the fixed covariates may be defined in an analogous way as for traditional path analysis. Theoretical considerations as well as simulations are presented, and a data set on recurrent bladder tumors is used to illustrate the methodology. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)