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 ...

Background Despite global efforts to improve nutrition, young women aged 15–24 years in low-income and middle-income countries (LMICs) face persistent dual burdens of malnutrition, marked by high ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems. Logistic regression is a technique used to make ...

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic ...

Individuals exposed to paternal passive smoke pre-puberty have risk for pre-COPD impaired lung function trajectories during the first 6 decades of life.

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover ...