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As a criterion for inclusion of variables in the multivariate analysis, we considered variables with a p value equal or less than 0.2 obtained in the bivariate analysis to allow potential confounding.
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We also used bivariate analysis to examine associations with socioeconomic indicators (Table 3).
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We used analysis of variance for bivariate analysis to explore associations and potential confounders.
After bivariate analysis to test the hypotheses using Pearson correlation, we performed multiple regression analysis.
We used univariate and bivariate analyses to describe the magnitude and pattern of abuse in the sample and bivariate analysis to identify risk factors for abuse.
We used bivariate analysis to compare adults hospitalized with influenza with and without pneumonia.
We performed bivariate analysis to examine associations between child's disease severity status and potential predictors.
We first performed bivariate analysis to determine parental and pregnancy characteristics associated with birth outcomes.
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To evaluate the crude association between functional dependency and the TSN, and the association among dependency and the other covariates, we performed a bivariate analysis that allowed estimating the crude prevalence ratios (PR) and 95% confidence intervals (95% CI).
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