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A binomial logistic regression model was used to evaluate the prognostic value (OR) of the categorical factors to the outcome and later seizure recurrence.
Furthermore, a scoring-function-based binomial logistic regression model for prediction of B. pseudomallei MIP inhibitors with submicromolar affinity is presented.
Furthermore, we tested the independent effect of gene methylation on tumor multiplicity by including all evaluated genes in the binomial logistic regression model, along with age and gender.
Multivariate analysis used forward likelihood binomial logistic regression model.
Mortality rates were investigated using a multilevel binomial logistic regression model, with 'Group' as a categorical predictor and random intercepts for practices.
Model 1: A binomial logistic regression model was used to determine associations between farm characteristics and the probability that a herd was seronegative for PRRSV antibodies.
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Data were analyzed using binomial logistic regression modeling designed to detect differential item functioning (DIF).
Binomial logistic regression models indicated that early access to substance use services matters (within two months of the temporary custody hearing) but only when parents were connected with a recovery coach.
Their binomial logistic regression models treated whether a trip was made on the weekday or the weekend as a travel characteristic variable along with four other binary variables relating to travel purposes.
Binomial logistic regression models were used to investigate associations for all six countries [ 60].
Table 4 provides statistical results from binomial logistic regression models computed for the dependent variable distance.
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