Sentence examples for bivariate analysis were fitted from inspiring English sources

Variables with p<0.2 in bivariate analysis were fitted into the final multiple logistic regression models.

Those variables with p-value ≤ 0.2 in the bivariate analysis were fitted to the multivariate Cox-proportional hazards model.

Variables found to be significant in the bivariate analysis were fitted to multivariate analysis to determine the main predictors.

Variables identified to be statistically significant in the bivariate analysis were fitted into a logistic regression model.

Following the results of multivariate logistic regression while adjusting for multiple co-variates, variables identified to be statistically significant in the bivariate analysis were fitted into a logistic regression model.

Variables which were found to be significant for association with rural choice of future practice location in bivariate analysis were further analyzed through logistic regression only after testing of model fit.

The variables with p values 0.25 in the bivariate analysis were included in the multivariable analysis and were kept in the model if they remained statistically significant (p < 0.05) or fitted to the model.

Descriptive statistics and bivariate analysis were used to assess the data.

Univariate and bivariate analysis were performed as appropriate.

Covariates significant at p < 0.05 in bivariate analysis were individually incorporated, ordered by strength of the bivariate correlation.

Bivariate analysis was computed and those variables whose p values less than or equal to 0.2 were fitted into the backward stepwise multivariate logistic regression model.