Sentence examples for multivariate analyses selected from inspiring English sources

Multivariate analyses selected high IMD level (OR, 1.089; 95% CI, 1.062 1.116; P < 0.001) and positive lymph node status (OR, 5.691; 95% CI, 2.846 11.379; P < 0.001) as the independent predictors for 5-year adverse event of BC women.

Covariate adjustments used in multivariate analyses were selected from a backward selection with a p-value less than 20%.

Second, to detect independent clinical factors predicting IST, univariate regression analyses were performed for all variables, followed by multivariate regression analyses selecting those variables that were associated with P values <0.10 in the univariate analyses.

Clinicopathologic factors taken into multivariate analyses were selected according to the significance of univariate analyses by Kaplan Meier methods.

Variables in Table 1 (additional file 1) were identified as potential predictors in our multivariate analyses and selected for screening to include in baseline multivariate models.

Bivariate and multivariate analyses using selected demographic variables showed only marginal relationships between race/ethnicity and sex/fasting status with serum ME concentrations.

Significant cut-lines for those factors were then explored, and candidates for multivariate analyses were selected and eliminated after considering Spearman's rank correlation coefficient.

Potential confounders/other risk factors for the bivariate and multivariate analyses were selected by testing for all other possible risk factors using χ2 tests (categorical variables) and retaining the one in each domain that was the most significant predictor for conviction for a violent crime.

Other differences regarding process measures disappeared in the multivariate analyses after adjusting for selected control variables.

If a study reported the results by both univariate and multivariate analyses, the latter was selected since it considered the confounding factors and was therefore more precise.

In selected cases, multivariate analyses were used to control for possible covariates of interest.