Artificial neural networks (ANNs) have found increasing usage in regression problems because of their ability to map complex nonlinear relationships. In recent years, ANN regression model applications ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

In a recent study posted to the medRxiv* preprint server, an interdisciplinary team of researchers from the United States (US) assessed predictions of the laboratory-confirmed coronavirus disease 2019 ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

Regression models predict outcomes like housing prices from various inputs. Machine learning enhances regression by analyzing large, complex datasets. Different regression types address varied data ...

Generalized estimating equations (GEEs) have been successfully used to estimate regression parameters from discrete longitudinal data. GEEs have been adapted for spatially correlated count data with ...