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Although our multivariate model works for two areas, this does not necessarily imply that more complex relationships between damage and dysfunction will allow the method to work for multiple critical areas.
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Many others: Students in the course Bayesian Inference Environm Models (BIO/ENV 665) at Duke University and members of the Multivariate Modeling working group of the SAMSI Ecology program contributed many ideas, recommendations, and feedback.
In multivariate models, work in the ART clinic (RR = 1.4, 95%CI = 1.0 – 1.6) and worry about becoming infected with HIV during their work (RR = 1.8, 95%CI 1.2 – 2.2) were significantly associated with HIV testing (Table 5).
However, in the multivariate model, cooks working in the biggest-scale kitchens were not shown to have an increased incidence of LBP.
In the final multivariate model not being in paid work, compulsory admission, BPRS Hostility/Suspiciousness and NPI-29 Entitlement/Uniqueness were significantly associated with high humiliation.
Multivariate modelling showed that working ≥49 h/week (23%) and working for ≤10 000 Bath/month (37%) were associated with workplace injury.
While statistically significant in univariate modelling, age, marital status, adequate sleep, working in a surgical department, years of working and shift work were eliminated in the multivariate model after adjusting for other variables.
In the multivariate model, high perceived physical exertion in domestic work remained significant predictor of future sick leave (Table 5).
Only the number of hours worked per week and the type of working hours showed statistical significance in the multivariate model for this profile.
Our multivariate model shows that the factors best associated with at-work productivity loss are drawn from all three domains.
Using linear regression analyses, a multivariate model was built containing the combination of factors best associated with at-work productivity loss.
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