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The multivariate logistic regression with backward method was performed for IL-6, IL-10, TNF-α, and age.
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Univariate and multivariate logistic regression analyses (stepwise backward method) were performed to look for associations between the studied parameters with foot ulceration.
A backward selection method was performed for model fitting and predictors with the highest p-value were taken out from the model one at a time until achievement of the most parsimonious model.
Multivariable analysis using the "backward Wald" method was performed to calculate odds ratios (ORs) and determine independent factors affecting survival.
After that, multiple linear regression analysis using the backward selection method was performed to estimate the effects of measures of obesity on cardiac structure alteration.
Binary logistic regression using the backward conditional method was performed on multiple factors to eliminate confounding and to examine the effect of the independent predictors of metabolic syndrome.
Binary logistic regression using the backward conditional method was performed on multiple factors to eliminate confounding and to examine the effect of independent predictors on the occurrence of metabolic syndrome.
Variables removed from the model when a backward stepwise method was performed and those known to be potential cofounders or factors associated with knowledge from previous studies were tested for confounding, any of the mentioned variables that had a more than ten percentage change (>10%) in the crude and adjusted odds ratio was considered a confounder.
To evaluate the risk factors related to the presence of drug-drug interactions in prescription mixes, a multiple logistic regression analysis by using the backward stepwise method was performed; the correlation terms and interactions among selected variables were also explored, and goodness of fit test was assessed for the best model.
Stepwise logistic regression using the backward elimination (likelihood ratio) method was performed to explore the best predictors of severe hypoglycemia.
Variables with p<0.10 in univariate analysis were included in multivariable analyses, and backward and forward selection methods were performed to identify significant variables at p<0.05 for any category of each variable.
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