April 12, 2007 Robust statistical analysis methods capable of dealing with large complex data sets are required more than ever before in almost all branches of science. The European Science Foundation ...
The newly developed Huber mean provides a more stable and reliable way to compute averages for data lying on curved geometric spaces, or Riemannian manifolds. By combining the strengths of ...
Cluster-robust inference and estimation methods have emerged as indispensable tools in empirical research, enabling statisticians and economists to draw valid conclusions from data exhibiting ...
Our laboratory has developed a range of data analysis workflows that incorporate advanced statistical and computational methods to interpret the complex molecular datasets generated by MS technologies ...
Dr Max Welz introduces research aiming to make statistical analyses robust against so-called ‘contamination’ in rating data stemming from low-quality survey responses. Empirical research in the social ...
A phase II, multi-center study of a new non-cytotoxic A3 adenosine receptor agonist CF101, dose-finding (randomized blinded) in patients (pts)with refractory metastatic colorectal cancer This is an ...
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-making. In both traditional ...
Faculty in the Statistics in Epidemiology Hub develop statistical methods to guide population-level research on cancer prevention, early detection, and real-world outcomes. Their work supports the ...
Chongzhi Di develops statistical methods for analyzing functional and longitudinal data in epidemiologic studies of physical activity and sedentary behavior, particularly using data from mobile-health ...
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