Sentence examples for bivariate analyses were in from inspiring English sources

In this study, bivariate analyses were in part exploratory; therefore, a P value of 0.008 (derived from the Bonferroni correction: 0.05/6 variables or groups of highly correlated variables) was deemed significant in these analyses.

All variables statistically significant at the p<0.05 levels in bivariate analyses were included in the multivariable models.

All variables statistically significant at the P < .05 levels in bivariate analyses were included in the multivariable models.

Non-collinear variables statistically significant at the p<0.05 level in bivariate analyses were included in the multivariate model.

Significant demographic, socioeconomic, other work environmental, and clinical factors identified in bivariate analyses were included in multivariate logistic regression modeling as potential confounders.

Variables which altered the OR point estimates by ≥10% in bivariate analyses were included in the multivariable logistic regression models for adjusted associations with HPV infection.

In order to adjust for potential confounding in the multivariable GEE analysis, variables significant at the p < 0.10 threshold in bivariate analyses were used in the backwards model selection process.

All covariates (except food consumption) with p ≤ 0.20 in bivariate analyses were included in an initial multivariable linear regression model for each OCP that was subsequently reduced to include predictors with p ≤ 0.10 only.

All predisposing and enabling factors that showed a statistically significant association with maternal oral health indicators in bivariate analyses were included in the multivariable models.Tthe ORs for having CPI ≥1 were higher for women aged 21 30 yrs (OR = 1.8, 95% CI 1.2-2.8), and 31 45 yrs (OR = 3.7, 95% CI 2.1-6.6 2.1-6.6ed with their comparedarts belowith yrs.

Significant factors related to non-participation in the tobacco prevention programme identified in the bivariate analyses were included in a multivariate analysis.

Variables with p < 0.2 in the bivariate analyses were entered in multivariate lineary regression analyses.