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We use binary logistic regression analyses in order to assess correlations between potential predictors and outcomes.
We always control for age, civil status and amount of children when we use binary logistic regression.
Since our dependent variable is dichotomous, we use binary logistic regression, again clustering standard errors by constituency.
Multinomial logistic regression models adjusting for sociodemographic and clinical factors provided estimates of the association between BMI levels and treatment use; binary logistic regression identified correlates of CAM use.
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In H2, the same binary-dependent variable used in H1, firm's propensity to repeat licensing, is regressed using binary logistic regression on the independent variable, RICV.
Completed surveys yielded 6541 responses which were analyzed using binary logistic regression.
Using binary logistic regression, PLEs were associated with a range of correlates across the five domains.
This article shows how such a landscape model can be established using binary logistic regression.
Adjusted odds ratios were calculated for each health outcome separately using binary logistic regression.
Statistical analysis was performed using binary logistic regression using log transformed data for all non-parametric variables (SPSS).
Using binary logistic regression, the probability of occurrence of suitable tsetse habitat decreased with increased distance from drainage lines.
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