2022
DOI: 10.1038/s41598-022-11498-w
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Latent class analysis of occupational accidents patterns among Iranian industry workers

Abstract: Occupational accidents (OA) are among the main causes of disabilities and death in developing and developed countries. The aims of this study were to identify the subgroups of OA and assess the independent role of demographic characteristics on the membership of participants in each latent class. This cross-sectional study was performed on 290 workers between 2011 and 2017. Data gathering was done using the reports of accidents recorded in filed lawsuits. Descriptive statistical analysis was done using SPSS 16… Show more

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Cited by 3 publications
(1 citation statement)
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“…These indices were likelihood-ratio statistics G2, Akaike information criteria (AIC), Bayesian information criteria (BIC), entropy, and log-likelihood value. Besides, the interpretability and parsimony of a model could help in the selection of the final model [ 12 ]. The sex of participants was considered as a grouping variable.…”
Section: Methodsmentioning
confidence: 99%
“…These indices were likelihood-ratio statistics G2, Akaike information criteria (AIC), Bayesian information criteria (BIC), entropy, and log-likelihood value. Besides, the interpretability and parsimony of a model could help in the selection of the final model [ 12 ]. The sex of participants was considered as a grouping variable.…”
Section: Methodsmentioning
confidence: 99%