Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...

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 ...

Unlock automatic understanding of text data! Join our hands-on workshop to explore how Python—and spaCy in particular—helps you process, annotate, and analyze text. This workshop is ideal for data ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Dataset: survey ratings (1–10 scale) Target variable: Writing Methods: CUB (in R), Proportional Odds Model (in Python) Goal: Compare model adequacy and interpret ordinal responses ...

ABSTRACT: Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure.

Neurointervention has seen significant advancements in recent decades with the adoption of myriad new technologies and techniques. Initially reliant on case reports and small case series, we now ...

We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...