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Statistical analysis was done using STATA12™.Independent variables identified as significant in a bivariate analysis were included as co-variates in a logistic regression model with outcome as the dependent variable.
All variables with p-values < = 0.25 in bivariate analysis were included in our multivariate model.
Variables with a significant association in bivariate analysis were included in a final logistic regression model.
All variables with a p-value less than 0.15 in bivariate analysis were included in the final model.
All the factors significantly associated with IA in the bivariate analysis were included in the logistic regression.
Those variables with p values of <0.05 in bivariate analysis were included in a simultaneous multivariate regression model to evaluate the significance of each predictor after controlling all the other predictors.
Only those variables of significance in the bivariate analysis were included in the multivariate analysis.
Variables with P value < 0.2 in bivariate analysis were included in multivariate analysis.
All variables that showed significant association during the bivariate analysis were included in the multivariate model.
All significant variables from the bivariate analysis were included in the multivariate logistic regression analysis.
Variables with P < 0.1 in bivariate analysis were included in the multivariable models.
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bivariate analysis were considered
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