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 ...

In this paper, we propose a user-friendly estimator to implement the method of difference-in-differences with ordinal ...

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 ...

Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL, USA. Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional ...

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 ...

Data analysis is the cornerstone of modern decision-making. It involves the systematic process of collecting, cleaning, transforming, and interpreting data to extract meaningful insights. By ...

Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...

it from this location: http://support.sas.com/kb/60678 and see the Downloads tab at that link. The code defining the CtoN macro and the code defining the macros below ...