Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.


Xiao Song

Evaluating biomarkers for treatment selection from reproducibility studies Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and…


He Tang

On estimation and order selection for multivariate extremes via clustering Abstract: We investigate the estimation of multivariate extreme models with a discrete spectral measure using clustering techniques. The primary innovation involves devising a method for selecting the appropriate order that not only consistently identifies the true order in theory but also has a straightforward and easy implementation in practice. Specifically, we…


Bimal Sinha

Confidence ellipsoids of a multivariate normal mean vector based on noise perturbed and synthetic data with applications Abstract: We discuss at length the problem of constructing a confidence ellipsoid of a multivariate normal mean vector based on a random sample from it. The central issue at hand is the sensitivity of the original micro data and hence the data cannot be directly used/analyzed. We consider a few perturbations of the original…


Hiya Banerjee

The Impact Of Treatment Discontinuation Due Adverse Events On Efficacy In An Oncology Clinical Trial Abstract Randomized clinical trials persist as the gold standard for evaluating the efficacy and safety of new treatments. However, in clinical trials of reasonable size and duration, it is common for some patients to deviate from their assigned study treatment due to various reasons. One such deviation is treatment discontinuation resulting from…


Ruiyan Luo

Fully Functional Neural Networks for Functional Regression Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard…


Xiaoming Zhai

AI and the formative Assesment: The Train Has Left the Station Abstract: Researchers have been questioning AI --whether we can and should use AI for formative assessment. AI is already being employed, for better or worse, to facilitate formative assessment in various educational contexts. In this talk, Dr. Zhai will demonstrate research on AI-based assessment in science education. He will respond to the many concerns raised in the field…


Partha Lahiri

The contribution of Joint Program in Survey Methodology (JPSM) to train graduate students in Survey and Data Science Abstract: The founding of JPSM in 1993 resulted from an initiative of the United States Federal Statistical Agency heads, the head of the Office of Management and Budget’s Statistical Policy Office, and the chair of the U.S. President’s Council of Economic Advisors. The founders of JPSM brought together a consortium of…


Richard A. Davis

Sample Splitting for Assessing Goodness of Fit in Time Series Abstract: A fundamental and often final step in time series modeling is to assess the quality of fit of a proposed model to the data. Since the underlying distribution of the innovations that generate a model is often not prescribed, goodness-of-fit tests typically take the form of testing the fitted residuals for serial independence. However, these fitted residuals are inherently…


Dr. Yishi Wang

Detecting True Lies, a Bayesian Approach for Modeling Veterans' Credibility using TOMM Abstract: The goal of this research is to evaluate the likelihood of credible responses from examinees, based on Performance validity tests (PVTs) scores from TOMM, the Test of Memory Malingering. Traditional research with TOMM adopts a single cutoff score. Recent studies suggest that different cutoff scores might be a better option, given various preexisting…


Pej Rohani

Early warning signals for disease re-emergence Abstract Developing statistical methods for anticipating the emergence or reemergence of infectious diseases is both important and timely; however, traditional model-based approaches are stymied by uncertainty surrounding the underlying drivers, especially in the context of disease (re-)emergence. In this talk, I will demonstrate an operational, mechanism-agnostic detection algorithm for disease (re…
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