The DOI matches its Crossref record; 17 of the 18 references it cites were found in a registry or an index.
Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
Open accessAbstract
Summary: The counting process with the Cox-type intensity function has been commonly used to analyse recurrent event data. This model essentially assumes that the underlying counting process is a time-transformed Poisson process and that the covariates have multiplicative effects on the mean and rate function of the counting process. Recently, Pepe and Cai, and Lawless and co-workers have proposed semiparametric procedures for making inferences about the mean and rate function of the counting process without the Poisson-type assumption. In this paper, we provide a rigorous justification of such robust procedures through modern empirical process theory. Furthermore, we present an approach to constructing simultaneous confidence bands for the mean function and describe a class of graphical and numerical techniques for checking the adequacy of the fitted mean–rate model. The advantages of the robust procedures are demonstrated through simulation studies. An illustration with multiple-infection data taken from a clinical study on chronic granulomatous disease is also provided.
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“An additional pre-specified analysis, the Andersen-Gill model using a Cox proportional-hazard with the counting-process formulation, was performed to model the total events (50,51).”
From Effects of Icosapent Ethyl on Total Ischemic Events (2019) · cites this paper as [51]
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Zannad, F., Ferreira, J. P., Pocock, S. J., Anker, S. D., Butler, J., Filippatos, G., Brueckmann, M., Ofstad, A. P., Pfarr, E., Jamal, W., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31824-9 · Cited by 1,408
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Metadata
- Authors
- Lin, D. Y., Wei, L. J., Yang, I., & Ying, Z.
- Affiliations
- University of Washington (US)
- Harvard University (US)
- Schering-Plough Research Institute , Kenilworth , USA
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Lin, D. Y.
- ORCID
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 2000-11-01
- Volume
- 62
- Issue
- 4
- Pages
- 711-730
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2012053212
- Cited by
- 969
- References
- 18
- Citations by year
- 2026: 47 · 2025: 67 · 2024: 70 · 2023: 57 · 2022: 56 · 2021: 51 · 2020: 55 · 2019: 44 · 2018: 53 · 2017: 38 · 2016: 36 · 2015: 45 · 2014: 55 · 2013: 38 · 2012: 38
- FWCI
- 10.55
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the Royal Statistical Society Series B (Statistical Methodology) (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UNC Libraries
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- recurrent event data, semiparametric regression, mean function, rate function, counting processes, empirical process theory, simultaneous confidence bands, model adequacy assessment, co-infection, chronic granulomatous disease
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