ABSTRACT: This study investigates the application of cumulative link models with alternative distributions (hyperbolic secant, Laplace, and Cauchy) to model ordinal outcomes of depressive severity ...

We often hear that “Who remembers the one who comes second?” The term ‘secondary’ is often associated with something less important, isn’t it? But today I tell you the importance of secondary in today ...

Abstract: Ordinal data—data that are ordered categories but do not assume equal spacing between values—are firmly entrenched in social and biomedical research. Ordinal data, regardless of their ...

AI Data Science Team is a Python library of specialized agents for common data science workflows, plus a flagship app: AI Pipeline Studio. The Studio turns your work into a visual, reproducible ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

Hello there! 👋 I'm Luca, a BI Developer with a passion for all things data, Proficient in Python, SQL and Power BI ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

Wrapping up a multi-week series on Crafting Data Personas. What are they, why are they important, and how to get started. Continuing from last week, we’re diving right into examples of personas. I ...