Additive mixed effect model for recurrent gap time data

Jieli Ding () and Liuquan Sun ()
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Jieli Ding: Wuhan University
Liuquan Sun: Chinese Academy of Sciences

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2017, vol. 23, issue 2, No 4, 223-253

Abstract: Abstract Gap times between recurrent events are often of primary interest in medical and observational studies. The additive hazards model, focusing on risk differences rather than risk ratios, has been widely used in practice. However, the marginal additive hazards model does not take the dependence among gap times into account. In this paper, we propose an additive mixed effect model to analyze gap time data, and the proposed model includes a subject-specific random effect to account for the dependence among the gap times. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite sample behavior of the proposed methods is evaluated through simulation studies, and an application to a data set from a clinic study on chronic granulomatous disease is provided.

Keywords: Additive mixed effect model; Estimating equation; Gap times; Random effects; Recurrent event data (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10985-015-9341-0

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