In this talk we present a statistical approach to evaluate the relationship between variables observed in a two-factors experiment. We consider a three-level model with covariance structure ${\bf \Sigma} \otimes {\bf \Psi}_1 \otimes {\bf \Psi}_2$, where ${\bf \Sigma}$ is an arbitrary positive definite covariance matrix, and ${\bf \Psi}_1$ and ${\bf \Psi}_2$ are both correlation matrices with...
Testing independence between functional observations remains a fundamental challenge in modern statistics, particularly in settings involving high-dimensional or infinite-dimensional random objects. The presented work introduces a new framework for independence testing in functional data based on the distance of mean embedding (DIME), a metric recently proposed as a flexible alternative to...
Evaluating a response variable in relation to exposure time or dose is a pivotal objective in the assessment of a compound's effect, particularly when determining toxicity in pre-clinical research or pharmacokinetics in clinical trials. The determination of an alert, such as the EC50 value, at which a pre-specified threshold of the response variable is crossed, is an important tool for the...
Introduction
Monitoring the clinical performance of healthcare units (e.g. hospitals, surgeons) is the main component for national audits, enabling identification of ‘outlier’ units whose clinical performance, e.g. in-hospital mortality, deviates significantly from expected performance. Accurate detection and subsequent management of outliers are critical for improving healthcare quality. ...
In many one-sample testing settings, one encounters the situation that the null hypothesis of interest is not precisely known. A prominent example arises in single-arm phase II trials, where the goal is to compare the response rate of a treatment to that of an established gold standard. In practice, the true response rate of the gold standard is virtually always unknown and hence must be...
