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Standard univariate and multivariate analyses using logistic regression were performed to describe predictors of adjuvant treatment.
We performed descriptive and multivariate analyses using the general linear model.
Multivariate analyses, using county as a random factor, show that both local- and landscape-scale factors were important.
Predictive factors for 90-day mortality were tested in univariate and multivariate analyses using a Cox proportional hazards model.
In the multivariate analyses, using logistic regression, we estimated the prevalence odds ratio (OR) with 95% confidence interval (CI) for the association between headache and caffeine consumption.
Multivariate analyses using principal component analysis and hierarchical cluster analysis revealed natural and anthropogenic activities as sources of heavy metal contamination in the borehole water samples.
Prognostic factors were examined by univariate and multivariate analyses using the Cox proportional hazards model.
Multivariate analyses using QIDS data from 2004 to 2007 reveal that underutilization averaged about 15% throughout the study period.
Univariate and multivariate analyses using Cox proportional hazards (PH) regression models were utilized to assess the effect of treatment on time to event [24].
Multivariate analyses using three different exposure indicators produced similar results.
Multivariate analyses using Cox proportional hazard model for survival is shown in Table 2.
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