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Variables associated with the platelet count with a p value <0.25 by bivariate analyses were included in a multivariate polytomic logistic regression to estimate their independent effect on platelet count.
Patient-physician encounter variables significant in bivariate analyses were included.
All variables statistically significant at the p<0.05 levels in bivariate analyses were included in the multivariable models.
Age, gender, and variables with p values < 0.2 in the bivariate analyses were included in the multivariate analysis [ 29].
Only variables which had a statistically significant association in the above bivariate analyses were included in the logistic regression.
Only significant diagnostic and other risk factor variables in the bivariate analyses were included in the multivariate analyses.
Similar(38)
For each dimension, only the variables found statistically significant in bivariate analyses are included in multivariate analysis.
All variables found to be significantly (p<0.10) associated with alcohol use in the bivariate logistic regression analyses were included in the multivariate logistic regression.
Variables significant at the 80%% significance level on bivariate analyses or conceptually fundamental to the analyses were included in multiple regression models.
Variables that were not significant at the 0.20 level in the bivariate analyses were not included.
Variables that were significantly associated with depressive symptoms in the bivariate analyses were then included in multilevel regression models.
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bivariate analyses were also
bivariate analyses were considered
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