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Joint frailty models for zero‐inflated recurrent events in the presence of a terminal event
Author(s) -
Liu Lei,
Huang Xuelin,
Yaroshinsky Alex,
Cormier Janice N.
Publication year - 2016
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12376
Subject(s) - event (particle physics) , censoring (clinical trials) , terminal (telecommunication) , zero (linguistics) , logistic regression , proportional hazards model , statistics , computer science , mathematics , telecommunications , linguistics , physics , philosophy , quantum mechanics
Summary Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of subjects without any recurrent events, manifesting the “zero‐inflated” nature of the data. Some of the zero events may be “structural zeros” as patients are unsusceptible to recurrent events, while others are “random zeros” due to censoring before any recurrent events. On the other hand, there often exists a terminal event which may be correlated with the recurrent events. In this article, we propose two joint frailty models for zero‐inflated recurrent events in the presence of a terminal event, combining a logistic model for “structural zero” status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times. The models can be fitted conveniently in SAS Proc NLMIXED. We apply the methods to model recurrent opportunistic diseases in the presence of death in an AIDS study, and tumor recurrences and a terminal event in a sarcoma study.