Sentence examples for bivariate analyses to identify from inspiring English sources

We conducted bivariate analyses to identify any demographic or practice characteristics associated with comfort levels.

We used bivariate analyses to identify variables potentially predicting the presentation of MI.

Model-building involved consideration of variables, using a series of bivariate analyses to identify potential confounders.

We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS.

Binary logistic regression was used to explore the relationship between intention to screen for bowel cancer and variables showing associations at the p = 0.30 level or less in bivariate analyses to identify independent predictors of screening intent.

We used bivariate analyses to identify differences in the receipt of preventive health services, including: cervical cancer screening, mammography, STI testing, safe sex counseling, influenza vaccination, TB testing, mental health screening, and substance abuse screening.

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 performed bivariate and multivariate analyses to identify risk factors for poor hemodynamic control during TJA.

Binary logistic regression model was further used for multivariate analyses to identify independent factors associated with CM use from the same variable tested in the bivariate analysis.

The bivariate analyses undertaken to identify confounding variables are presented in Table 2.

Bivariate analyses were conducted to identify significant relationships for inclusion of research variables in multivariate linear analyses (eg, stepwise regression to determine the best fitting predictive model for CG-CAHPS ratings).