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Heterogeneity and event dependence in the analysis of sickness absence
BACKGROUND: 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 mode...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852331/ https://www.ncbi.nlm.nih.gov/pubmed/24040880 http://dx.doi.org/10.1186/1471-2288-13-114 |
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author | Torá-Rocamora, Isabel Gimeno, David Delclos, George Benavides, Fernando G Manzanera, Rafael Jardí, Josefina Alberti, Constança Yasui, Yutaka Martínez, José Miguel |
author_facet | Torá-Rocamora, Isabel Gimeno, David Delclos, George Benavides, Fernando G Manzanera, Rafael Jardí, Josefina Alberti, Constança Yasui, Yutaka Martínez, José Miguel |
author_sort | Torá-Rocamora, Isabel |
collection | PubMed |
description | BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events, especially with large databases. |
format | Online Article Text |
id | pubmed-3852331 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-38523312013-12-19 Heterogeneity and event dependence in the analysis of sickness absence Torá-Rocamora, Isabel Gimeno, David Delclos, George Benavides, Fernando G Manzanera, Rafael Jardí, Josefina Alberti, Constança Yasui, Yutaka Martínez, José Miguel BMC Med Res Methodol Research Article BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events, especially with large databases. BioMed Central 2013-09-16 /pmc/articles/PMC3852331/ /pubmed/24040880 http://dx.doi.org/10.1186/1471-2288-13-114 Text en Copyright © 2013 Torá-Rocamora et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Torá-Rocamora, Isabel Gimeno, David Delclos, George Benavides, Fernando G Manzanera, Rafael Jardí, Josefina Alberti, Constança Yasui, Yutaka Martínez, José Miguel Heterogeneity and event dependence in the analysis of sickness absence |
title | Heterogeneity and event dependence in the analysis of sickness absence |
title_full | Heterogeneity and event dependence in the analysis of sickness absence |
title_fullStr | Heterogeneity and event dependence in the analysis of sickness absence |
title_full_unstemmed | Heterogeneity and event dependence in the analysis of sickness absence |
title_short | Heterogeneity and event dependence in the analysis of sickness absence |
title_sort | heterogeneity and event dependence in the analysis of sickness absence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852331/ https://www.ncbi.nlm.nih.gov/pubmed/24040880 http://dx.doi.org/10.1186/1471-2288-13-114 |
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