Test equating constitutes a critical element of modern assessment practices, ensuring that scores from different test forms are directly comparable. Recent advancements have pooled statistical ...

Our lab has developed many data analysis workflows adapting and integrating sophisticated statistical methods to evaluate complex molecular datasets that we obtain with MS technologies. We are ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

The goal of statistical scale space analysis is to extract scale-dependent features from noisy data. The data could be for example an observed time series or digital image in which case features in ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have ...

This workshop will explore opportunities to use statistical and data-driven methods for additive manufacturing qualification, including approaches that enhance dimensional accuracy and recent advances ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...