Please use this identifier to cite or link to this item: https://doi.org/10.1002/bimj.201100154
Title: Estimation and interpretation of incidence rate difference for recurrent events when the estimation model is misspecified
Authors: Xu, Y. 
Cheung, Y.B. 
Lam, K.F.
Milligan, P.
Keywords: Additive rate model
Incidence rate difference
Multiplicative rate model
Recurrent events
Time-varying covariate effects
Issue Date: Nov-2012
Citation: Xu, Y., Cheung, Y.B., Lam, K.F., Milligan, P. (2012-11). Estimation and interpretation of incidence rate difference for recurrent events when the estimation model is misspecified. Biometrical Journal 54 (6) : 750-765. ScholarBank@NUS Repository. https://doi.org/10.1002/bimj.201100154
Abstract: Recurrent events data are common in experimental and observational studies. It is often of interest to estimate the effect of an intervention on the incidence rate of the recurrent events. The incidence rate difference is a useful measure of intervention effect. A weighted least squares estimator of the incidence rate difference for recurrent events was recently proposed for an additive rate model in which both the baseline incidence rate and the covariate effects were constant over time. In this article, we relax this model assumption and examine the properties of the estimator under the additive and multiplicative rate models assumption in which the baseline incidence rate and covariate effects may vary over time. We show analytically and numerically that the estimator gives an appropriate summary measure of the time-varying covariate effects. In particular, when the underlying covariate effects are additive and time-varying, the estimator consistently estimates the weighted average of the covariate effects over time. When the underlying covariate effects are multiplicative and time-varying, and if there is only one binary covariate indicating the intervention status, the estimator consistently estimates the weighted average of the underlying incidence rate difference between the intervention and control groups over time. We illustrate the method with data from a randomized vaccine trial. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Source Title: Biometrical Journal
URI: http://scholarbank.nus.edu.sg/handle/10635/110063
ISSN: 03233847
DOI: 10.1002/bimj.201100154
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