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Comparison of the Andersen-Gill model with poisson and negative binomial regression on recurrent event data

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  • Jahn-Eimermacher, Antje

Abstract

Many generalizations of the Cox proportional hazard method have been elaborated to analyse recurrent event data. The Andersen-Gill model was proposed to handle event data following Poisson processes. This method is compared with non-survival approaches, such as Poisson and negative binomial regression. The comparison is performed on data simulated according to various event-generating processes and differing in subject heterogeneity. When robust standard error estimates are applied, for Poisson processes the Andersen-Gill approach is comparable to a negative binomial regression, whereas the poisson regression has comparable coverage probabilities of confidence intervals, but increased type I error rates; however, none of the methods can generate unbiased parameter estimates with data violating the independent increment assumption. These findings are illustrated by data from a clinical trial of the efficacy of a new pneumococcal vaccine for prevention of otitis media.

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  • Jahn-Eimermacher, Antje, 2008. "Comparison of the Andersen-Gill model with poisson and negative binomial regression on recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4989-4997, July.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:11:p:4989-4997
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    1. N/A, 1996. "Events," Psychology and Developing Societies, , vol. 8(2), pages 287-288, September.
    2. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
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    1. Babykina, Génia & Couallier, Vincent, 2012. "Empirical assessment of the Maximum Likelihood Estimator quality in a parametric counting process model for recurrent events," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 297-315.

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