Data analysis shows over half of Winter Olympic medal variation can be explained by climate, GDP per capita and population ...
Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...
Background Despite several intensive interventions, HIV remains a major public health challenge affecting many individuals worldwide and highlighting ongoing gaps in HIV testing. Objectives To assess ...
Hicksian demand refers to the quantity of a good a consumer would purchase after a price change, assuming their utility, or ...
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 ...
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 ...
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: Statistical analysis of largescale data is useful as it enables the extraction of a large amount of information, despite its simplicity. Therefore, fusing and analyzing data from different ...
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 ...
This macro performs an ordinal cluster analysis on a given dataset. It processes the data to compute win fractions, conducts a mixed model regression on these win fractions, and fits a proportional ...
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