Analysis of zero inflated dichotomous variables from a Bayesian perspective : application to occupational health
Moriña, David (Centre de Recerca Matemàtica)
Puig, Pedro (Universitat Autònoma de Barcelona. Departament de Matemàtiques)
Navarro Giné, Albert (Universitat Autònoma de Barcelona. Departament de Pediatria, Obstetrícia i Ginecologia i Medicina Preventiva i Salut Pública)

Data:	2021
Resum:	Background: Zero-inflated models are generally aimed to addressing the problem that arises from having two different sources that generate the zero values observed in a distribution. In practice, this is due to the fact that the population studied actually consists of two subpopulations: one in which the value zero is by default (structural zero) and the other is circumstantial (sample zero). Methods: This work proposes a new methodology to fit zero inflated Bernoulli data from a Bayesian approach, able to distinguish between two potential sources of zeros (structural and non-structural). Results: The proposed methodology performance has been evaluated through a comprehensive simulation study, and it has been compiled as an R package freely available to the community. Its usage is illustrated by means of a real example from the field of occupational health as the phenomenon of sickness presenteeism, in which it is reasonable to think that some individuals will never be at risk of suffering it because they have not been sick in the period of study (structural zeros). Without separating structural and non-structural zeros one would be studying jointly the general health status and the presenteeism itself, and therefore obtaining potentially biased estimates as the phenomenon is being implicitly underestimated by diluting it into the general health status. Conclusions: The proposed methodology is able to distinguish two different sources of zeros (structural and non-structural) from dichotomous data with or without covariates in a Bayesian framework, and has been made available to any interested researcher in the form of the bayesZIB R package (https://cran. r-project. org/package=bayesZIB).
Ajuts:	Agencia Estatal de Investigación RTI2018-096072-B-I00 Agencia Estatal de Investigación CEX2020-001084-M
Drets:	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.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Presenteeism ; Bayesian methods ; Zero-infation ; Simulation study ; Bernoulli mixture models
Publicat a:	BMC Medical Research Methodology, Vol. 21 Núm. 1 (december 2021) , p. 277, ISSN 1471-2288

DOI: 10.1186/s12874-021-01427-2
PMID: 34895155

9 p, 1.2 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Research group on Psychosocial Risks, Organization of Work, and Health (POWAH)
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