examine the gains in precision using interval-level measures relative to ordinal scores when discriminating between groups known to differ in disability. Design Cross-sectional, population-based study ...

treating the samples as groups disregards the fact that tar is measured on an interval scale, not a categorical scale; not taking advantage of this fact would reduce the power of the analysis. Second, ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

Welcome to your gateway to the IMF's global economic data. Our new data portal provides streamlined access to timely, reliable, and easy-to-understand macroeconomic and financial data. While the ...

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: 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 ...

Variance is a measurement of dispersion across a data set, comparing the difference between every other number in the set. Variance is a statistical measurement of how large of a spread there is ...

Abstract: The cyber security of large-scale smart grid against false data injection attack (FDIA) is concerned in this article. FDIA can modify the sensor data and make internal states cause bias ...

However, the data collected from industrial plants are usually sampled with irregular frequency, making it challenging for traditional methods to handle these temporally changeable relationships.

The author has completed the ICMJE form and declares no conflicts of interest. Article Many studies include ordinal data, such as the integers from 1 to 4. Can the mean or median be a relevant summary ...