Background To investigate prevalence and risk factors of epiretinal membrane (ERM), particularly those associated with ERM ...

Understanding moment-to-moment therapeutic change is critical for advancing psychological interventions, yet existing tools rarely capture these dynamics. Dynamical systems theory offers a ...

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 ...

Introduction The importance of conducting qualitative research alongside clinical trials of complex healthcare interventions is well established. There are various ways in which these two ...

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 ...

This article adopts a constructivist grounded theory approach based on the principle of intersubjective relations and the co-construction of interpretations. Reflecting on the author's experiences as ...

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 ...

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...

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 ...

Abstract: This paper introduces a novel framework for Archetypal Analysis (AA) tailored to ordinal data, particularly from questionnaires. Unlike existing methods, the proposed method, Ordinal ...