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Additive–multiplicative rates model for recurrent events

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Abstract

Recurrent events are frequently encountered in biomedical studies. Evaluating the covariates effects on the marginal recurrent event rate is of practical interest. There are mainly two types of rate models for the recurrent event data: the multiplicative rates model and the additive rates model. We consider a more flexible additive–multiplicative rates model for analysis of recurrent event data, wherein some covariate effects are additive while others are multiplicative. We formulate estimating equations for estimating the regression parameters. The estimators for these regression parameters are shown to be consistent and asymptotically normally distributed under appropriate regularity conditions. Moreover, the estimator of the baseline mean function is proposed and its large sample properties are investigated. We also conduct simulation studies to evaluate the finite sample behavior of the proposed estimators. A medical study of patients with cystic fibrosis suffered from recurrent pulmonary exacerbations is provided for illustration of the proposed method.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China

    Yanyan Liu & Yuanshan Wu

  2. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7420, USA

    Yuanshan Wu, Jianwen Cai & Haibo Zhou

Authors
  1. Yanyan Liu
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  2. Yuanshan Wu
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  3. Jianwen Cai
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  4. Haibo Zhou
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Correspondence to Jianwen Cai.

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Liu, Y., Wu, Y., Cai, J. et al. Additive–multiplicative rates model for recurrent events. Lifetime Data Anal 16, 353–373 (2010). https://doi.org/10.1007/s10985-010-9160-2

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  • DOI: https://doi.org/10.1007/s10985-010-9160-2

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