Please use this identifier to cite or link to this item: https://doi.org/10.1002/sim.3783
Title: Estimation of intervention effects using first or multiple episodes in clinical trials: The Andersen-Gill model re-examined
Authors: Cheung, Y.B. 
Xu, Y.
Tan, S.H.
Cutts, F.
Milligan, P.
Keywords: Efficacy
Event dependency
Heterogeneity
Recurrent event
Survival analysis
Vaccines
Issue Date: 10-Feb-2010
Source: Cheung, Y.B., Xu, Y., Tan, S.H., Cutts, F., Milligan, P. (2010-02-10). Estimation of intervention effects using first or multiple episodes in clinical trials: The Andersen-Gill model re-examined. Statistics in Medicine 29 (3) : 328-336. ScholarBank@NUS Repository. https://doi.org/10.1002/sim.3783
Abstract: Randomized trials of interventions against infectious diseases are often analyzed using data on first or only episodes of disease, even when subsequent episodes have been recorded. It is often said that the Andersen-Gill (AG) model gives a biased estimate of intervention effect if there is event dependency over time. We demonstrate that, in the presence of event dependency, an effective intervention may have an indirect effect on disease risk at time tj via its direct effect on disease risk at time ti, i
Source Title: Statistics in Medicine
URI: http://scholarbank.nus.edu.sg/handle/10635/110064
ISSN: 02776715
DOI: 10.1002/sim.3783
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