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Semiparametric estimation of time‐varying intervention effects using recurrent event data
Author(s) -
Xu Jiajun,
Lam K. F.,
Chen Feng,
Milligan Paul,
Cheung Yin Bun
Publication year - 2017
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7319
Subject(s) - estimation , statistics , computer science , booster (rocketry) , guideline , event data , malaria , piperaquine , econometrics , medicine , mathematics , plasmodium falciparum , artemisinin , covariate , immunology , physics , management , astronomy , economics , pathology
We consider the estimation of the optimal interval between doses for interventions such as malaria chemoprevention and vaccine booster doses that are applied intermittently in infectious disease control. A flexible exponential‐like function to model the time‐varying intervention effect in the framework of Andersen–Gill model for recurrent event time data is considered. The partial likelihood estimation approach is adopted, and a large scale simulation study is carried out to evaluate the performance of the proposed method. A simple guideline for the choice of the optimal interval between successive doses is proposed. The methodology is illustrated with the analysis of data from a malaria chemoprevention trial. Copyright © 2017 John Wiley & Sons, Ltd.