Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

A comparison of logistic functions. Logistic regression models have one dependent variable and several independent categorical or continuous predictor variables. Unlike standard linear regression ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...

Blood-based protein signatures showed high accuracy in classifying forms of hypertension, supporting a shift toward precision ...

A model with eight independent risk factors can predict the risk for deep vein thrombosis (DVT) in patients with epithelial ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

Artificial Neural Network(Ann) and logistic regression (LR) models were selected to predict the risk of OILI, and the performance of the two models was evaluated and compared, in the expectation ...

Logistic regression is the appropriate tool for such an investigation. Note that Model Pr{ }: determines which value of the dependent variable the model is based on; usually, the value representing an ...