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For outcomes that changed significantly between the two surveys in bivariate analysis, we constructed multivariate models to examine whether this change over time could be explained by other variables related to the outcome.
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For bivariate analysis, we included the trait TG as well.
After bivariate analysis, we conducted a multivariable analysis.
After bivariate analysis, we conducted a multivariable analysis using forward selection techniques.
For bivariate analysis, we computed odds ratios and confidence intervals using the trend chi squared test.
In a bivariate analysis we found no significant gender differences regarding the total number of diseases.
Using bivariate analysis, we summarized GM TBHg concentrations by covariate, and participant characteristics by hepatitis status.
In bivariate analysis, we used χ test and Fisher's exact test for categorical variables.
In the bivariate analysis we will investigate the diagnostic accuracy of single symptoms and signs.
Using bivariate analysis, we compared a number of environmental characteristics between the two racial groups.
Similar to the bivariate analysis we will use a stepwise approach.
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