Abstract: The quality of modern software relies heavily on the effective use of static code analysis tools. To improve their usefulness, these tools should be evaluated using a framework that ...

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 ...

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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 ...

If you’re new to Python, one of the first things you’ll encounter is variables and data types. Understanding how Python handles data is essential for writing clean, efficient, and bug-free programs.

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 ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

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.

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

NSCLC in the immunotherapy era: Trends in survival and disparities across demographic and socioeconomic groups. Prediction of IO response combining clinical parameters, intra- & peritumoral CT ...