miRecSurv Package: Prentice-Williams-Peterson Models with Multiple Imputation of Unknown Number of Previous Episodes
Moriña, David (Universitat de Barcelona. Departament d'Econometria, Estadística i Economia Aplicada)
Hernández Herrera, Gilma (Universidad de Antioquia. Instituto de Investigaciones Médicas)
Navarro Giné, Albert (Universitat Autònoma de Barcelona. Departament de Pediatria, Obstetrícia i Ginecologia i Medicina Preventiva i Salut Pública)
Universitat Autònoma de Barcelona. Research group on Psychosocial risks, Organization of Work and Health (POWAH)

Date:	2021
Abstract:	Left censoring can occur with relative frequency when analyzing recurrent events in epidemiological studies, especially observational ones. Concretely, the inclusion of individuals that were already at risk before the effective initiation in a cohort study may cause the unawareness of prior episodes that have already been experienced, and this will easily lead to biased and inefficient estimates. The miRecSurv package is based on the use of models with specific baseline hazard, with multiple imputation of the number of prior episodes when unknown by means of the COMPoisson distribution, a very flexible count distribution that can handle over, sub, and equidispersion, with a stratified model depending on whether the individual had or had not previously been at risk, and the use of a frailty term. The usage of the package is illustrated by means of a real data example based on an occupational cohort study and a simulation study.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Published in:	The R Journal, Vol. 13 Num.2 (2021) , pag. 419-426, ISSN 2073-4859

8 p, 240.1 KB

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Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Research group on Psychosocial Risks, Organization of Work, and Health (POWAH)
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