Sentence examples for bivariate analysis were considered from inspiring English sources

Variables with P < 0.10 in bivariate analysis were considered for inclusion in the models.

Variables that presented p ≤ 0.20 in bivariate analysis were considered for the multivariate multilevel analysis.

Variables with a P value < 0.1 in the bivariate analysis were considered for inclusion in the multivariate model.

The variables which were significant at P < 0.25, at Bivariate analysis were considered for stepwise logistic regression analysis.

All variables with p value of less than 0.02 in the bivariate analysis were considered for multivariate analysis.

During modeling for regression analyses, all variables of clinical importance or with p-value 0.2 and less on bivariate analysis were considered for inclusion.

Multivariate logistic regression analysis was performed, and we included in the model variables showing a statistically significant association (p<0.05) with the outcome in the bivariate analysis and a variable that, although not statistically significant in the bivariate analysis, was considered an important contributor to STI risk (ie, history of sex work).

All bivariate and multivariate analysis were considered significant if p < 0.05.

Variables that were statistically significant (p value <0.05) in the bivariate analysis were subsequently considered for multivariate analysis (Cox proportional hazard model) to assess the relationship between these variables and mortality.

In the same model, other variables that did not reach a statistical significance level on bivariate analysis but were considered clinically important based on experience were also added.

Therefore, the bivariate analysis was done considering the data as a pool across studies to estimate associations rather than accounting for the correlation between studies as done for the shedding outcome.