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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.

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Modeling Cumulative Incidences of Dementia and Dementia-Free Death Using a Novel Three-Parameter Logistic Function

Yu Cheng1

1University of Pittsburgh

Citation Information: The International Journal of Biostatistics. Volume 5, Issue 1, ISSN (Online) 1557-4679, DOI: https://doi.org/10.2202/1557-4679.1183, November 2009

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Parametric modeling of univariate cumulative incidence functions and logistic models have been studied extensively. However, to the best of our knowledge, there is no study using logistic models to characterize cumulative incidence functions. In this paper, we propose a novel parametric model which is an extension of a widely-used four-parameter logistic function for dose-response curves. The modified model can accommodate various shapes of cumulative incidence functions and be easily implemented using standard statistical software. The simulation studies demonstrate that the proposed model is as efficient as or more efficient than its nonparametric counterpart when it is correctly specified, and outperforms the existing Gompertz model when the underlying cumulative incidence function is sigmoidal. The practical utility of the modified three-parameter logistic model is illustrated using the data from the Cache County Study of dementia.

Keywords: cause-specific hazard function; cumulative incidence function; long-term incidence; modified three-parameter logistic mode; parametric modeling

Citing Articles

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Haiwen Shi, Yu Cheng, and Jong-Hyeon Jeong
Biometrical Journal, 2013, Volume 55, Number 1, Page 82
Yu Cheng and Jason P. Fine
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2012, Volume 74, Number 2, Page 183

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