U.S. military service was associated with a lowered risk for depression, particularly when considering factors such as age, ...

Establishing binary logistic regression allowed researchers to study the marginal impacts of the predictor variables on the phenomenon studied (i.e., ORs) and propose the SWICS-30 score.

Factors associated with GBV Binary logistic regression was fitted to identify factors that had an association with GBV. Consequently, eight variables with a p -value of less than 0.2 during bivariable ...

For binary logistic regression, dependent variables must be binary, while ordinal logistic regression requires ordinal dependent variables—variables that occur in natural, ordered categories.

In relation to the clinical variables of the newborn, significant differences were only present the height in centimeters (p =0.05). From the significant findings of the bivariate analysis, a ...

Due to the large number of predictors and the relatively small sample size, elastic net logistic regression with nested cross-validation (nested CV) is a viable method to address the issues of ...

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...

The need for ethical data scientists in today's society is greater than ever before. The Online Master of Science (M.S.) in Data Science empowers you to apply technical methods and consulting skills ...

Additionally, a binary logistic regression model was used to analyze the socioeconomic factors related to LULC change in DNPF. Key findings indicated a decline in natural forest areas within the study ...