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Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury.
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Van Calster et. al. [ 12] described several AUC score estimation methods for the ordinal logistic model, one of which is to use the mean of AUC scores from K − 1 binary logistic regression estimations to serve as the AUC score for ordinal logistic model.
The next three regressions were binary logistic regressions.
†In these binary logistic regressions, the regression coefficient = ln(OR).
This outcome was adjusted for confounders in binary logistic regressions.
Binary logistic regressions were used as means of analyses.
Group differences were tested by binary logistic regressions.
Both bivariate and multivariable analyses (binary logistic regressions) are presented.
Binary logistic regressions were used to examine both hypotheses.
Table 4 Binary logistic regression results.
Binary logistic regression was applied [18].
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