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Related to bivariate analysis: multivariate analysis, univariate analysis
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Bivariate analysis found no statistically significant correlation with any cervical risk factor.
Table 2 shows the bivariate analysis of the demographic and RA related variables in patients with and without OP.
Bivariate analysis was performed on 1 136 study participants for whom complete data on incontinence outcomes were available.
While meta-analyses in entrepreneurship commonly apply bivariate analysis techniques [32,39].
Bivariate analysis identified factors associated with having influenza A(H1N1)pdm09.
In bivariate analysis, the OR for a one-unit change in log-transformed mean prenatal BPA concentration was 1.
In bivariate analysis, 7 of 12 of the baseline predictor variables were significant at T1: baseline remission, total number of intimates, community integration, residential status, self-esteem score, number of psychiatric medications, and number of entitlements.
After taking the age group of 12-14 years as the reference category the bivariate analysis found that girls who had menarche at 15 years and above had a 30% higher chance of reporting dysmenorrhea when compared to girls who had menarche at 12-14 years and the difference was found to be statistically significant (RR: 1.
For individuals with data from both the dental examination and the questionnaire survey, as the data were not normally distributed, a process of bivariate analysis for non-parametric data was undertaken using the exact versions of Chi-squared, Fisher's and linear association tests.
Significant variables after bivariate analysis were further investigated using multivariate analysis.