Heterogeneity and event dependence in the analysis of sickness absence

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• dc.contributor.author Torá Rocamora, Isabel, 1979-ca
• dc.contributor.author Gimeno Ruiz de Porras, Daviden
• dc.contributor.author Delclòs i Clanchet, Jordi, 1956-ca
• dc.contributor.author Benavides, Fernando G. (Fernando García)ca
• dc.contributor.author Manzanera, Rafaelen
• dc.contributor.author Jardí, Josefinaen
• dc.contributor.author Alberti, Constançaca
• dc.contributor.author Yasui, Yutakaca
• dc.contributor.author Martínez Martínez, José Miguel, 1974-ca
• dc.date.accessioned 2013-11-28T11:32:30Z
• dc.date.available 2013-11-28T11:32:30Z
• dc.date.issued 2013ca
• dc.description.abstract Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration. To overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders. As expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM. The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events,/nespecially with large databases.
• dc.description.sponsorship This work was supported by grants from the Fondo de Investigación/nSanitaria [PI11/01470], Operating Grant of the Canadian Institute of Health Research entitled 'Statistical Methods for Epidemiologic Investigations' and the Institut Català d'Avaluacions Mèdiques.en
• dc.format.mimetype application/pdfca
• dc.identifier.citation Torá-Rocamora I, Gimeno D, Delclos G, Benavides FG, Manzanera R, Jardí , et al. Heterogeneity and event dependence in the analysis of sickness absence. BMC Med. Res. Methodol. 2013;13(1):114. DOI: 10.1186/1471-2288-13-114ca
• dc.identifier.doi http://dx.doi.org/10.1186/1471-2288-13-114
• dc.identifier.issn 1471-2288ca
• dc.identifier.uri http://hdl.handle.net/10230/21318
• dc.language.iso engca
• dc.publisher BioMed Centralca
• dc.relation.ispartof BMC Medical Research Methodology. 2013;13(1):114
• dc.rights © Torá-Rocamora et al. Creative Commons Attribution Licenseca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.rights.uri http://creativecommons.org/licenses/by/2.0/
• dc.subject.keyword Sickness absence
• dc.subject.keyword Survival analysis
• dc.subject.keyword Conditional frailty model
• dc.subject.keyword Poisson regression
• dc.subject.keyword Mental disorders
• dc.subject.keyword Neoplasms
• dc.title Heterogeneity and event dependence in the analysis of sickness absenceca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca