YSPH Biostatistics Seminar: “Feature Aggregation in Causal Discovery for High-dimensional Data: Application to Targeting the “Gut-Brain-Axis” via the Microbiome Diversity"
Jinyuan Liu, PhD, Assistant Professor, Department of Biostatistics, Vanderbilt University Medical Center
September 19, 2023
YSPH Biostatistics Seminar: “Network analysis for understanding complex predictors in complex diseases: an example from proteomics in Alzheimer's Disease"
Meghan Short, PhD, Assistant Professor of Medicine, Tufts University School of Medicine; Faculty: Institute for Clinical Research and Health Policy Studies (ICRHPS); Faculty: Biostatistics, Epidemiology, and Research Design (BERD), Tufts Clinical and Translational Sciences Institute (CTSI)
September 12, 2023
YSPH Biostatistics Seminar: “A Sequential Basket Trial Design Based on Multi-Source Exchangeability with Predictive Probability Monitoring”
Dr. Alex Kaizer, Assistant Professor, Center for Innovative Design and Analysis (CIDA) Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus
November 15, 2022
YSPH Biostatistics Seminar: “The Predictive Individual Effect for Survival Data: A Patient-Oriented Summary Measure for Treatment Benefit”
Speaker: Satrajit Roychoudhury, PhD, Pfizer
November 8, 2022
YSPH Biostatistics Seminar: “Opening Black Boxes: Enhancing Statistical Rigor in Genomics Data Science”
Speaker: Jingyi Jessica Li, PhD, Associate Professor, Department of Statistics, University of California, Los Angeles
October 11, 2022
YSPH Biostatistics Seminar: “Estimation and Inference for Networks of Multi-Experiment Point Processes”
Speaker: Ali Shojaie, PhD, Professor of Biostatistics, Adjunct Professor of Statistics, University of Washington
October 4, 2022
Speaker: Yiwen Liu, PhD, Assistant Professor, Department of Epidemiology and Biostatistics, University of Arizona
September 27, 2022
YSPH Biostatistics Seminar: “Robust Mendelian Randomization in the Presence of Many Weak Instruments and Widespread Horizontal Pleiotropy”
Speaker: Ting Ye, PhD, Assistant Professor, Department of Biostatistics, University of Washington
September 20, 2022
Alexander Strang, Kruskal Instructor, Statistics and Applied Math, University of Chicago
September 12, 2022
YSPH Biostatistics Seminar: "SPRUCE and MAPLE: Bayesian Spatial Multivariate Mixture Model for High Throughput Spatial Transcriptomics Data"
Dongjun Chung, PhD, Associate Professor, Department of Biomedical Informatics, The Ohio State University
November 30, 2021
Brian P. Hobbs, PhD, Associate Professor, Department of Population Health, University of Texas at Austin
December 7, 2021
YSPH Biostatistics Seminar: "Measures of Selection Bias for Proportions Estimated from Non-Probability Samples"
Rebecca Andridge, PhD, Associate Professor, Department of Biostatistics, The Ohio State University
November 16, 2021
YSPH Biostatistics Seminar: "Innovations in Immune-Oncology Early-Phase Trial Designs: Theory, Practice and Next Steps"
Codruta Chiuzan, PhD, Associate Professor, Center for Personalized Health, Institute of Health System Science, The Feinstein Institutes for Medical Research, Northwell Health
November 2, 2021
YSPH Biostatistics Seminar: "Exploring Space and Time for Identifying Gene Interactions Using Single-cell Transcriptomics"
Atul Deshpande, PhD, Postdoctoral Researcher, Division of Biostatistics and Bioinformatics, Johns Hopkins University
October 5, 2021
Andrew Holbrook, PhD, Assistant Professor, Department of Biostatistics, University of California, Los Angeles
September 28, 2021
YSPH Biostatistics Seminar: “Addressing the Replicability and Generalizability of Clinical Prediction Models”
Naim Rashid, PhD
Associate Professor, Department of Biostatistics
University of North Carolina at Chapel Hill
September 7, 2021
YSPH Biostatistics Virtual Seminar: "Telehealth Use to Support Management of Anxiety and Depression Among African American Women"
Terika McCall, PhD, MPH, MBA
Center for Medical Informatics
Yale School of Medicine
Jessica Young, Ph.D
Department of Population Medicine
Harvard Medical School
March 23, 2021
Matthew Stephens, PhD, Ralph W. Gerard Professor Department of Statistics, Human Genetics and the College
The University of Chicago
March 2, 2021
Xihong Lin, PhD
Professor, Department of Biostatistics
Harvard T.H. Chan School of Public Health
Tuesday, February 23, 2021
Jingshu Wang, Ph.D.
Department of Statistics and the College
The University of Chicago
Tuesday, February 9, 2021
Eugene Katsevich, Ph.D.
Assistant Professor in the Department of Statistics
The Wharton School at the University of Pennsylvania
YSPH Biostatistics Seminar: “Marginal Structural Models for Causal Inference with Continuous-Time Treatment and Censored Survival Outcomes"
Liangyuan Hu, PhD, Assistant Professor - Department of Population Health Science and Policy
Icahn School of Medicine at Mount Sinai
December 8, 2020
Biostatistics Seminar - November 17, 2020
Elizabeth Tipton, PhD
Associate Professor, Department of Statistics, Northwestern University
YSPH Biostatistics Virtual Seminar: “Optimal Doubly Robust Estimation of Heterogeneous Causal Effects"
Edward Kennedy, PhD
Assistant Professor, Department of Statistics & Data Science, Carnegie Mellon University
Abstract: Heterogeneous effect estimation plays a crucial role in causal inference, with applications across medicine and social science. Many methods for estimating conditional average treatment effects (CATEs) have been proposed in recent years, but there are important theoretical gaps in understanding if and when such methods are optimal. This is especially true when the CATE has nontrivial structure (e.g., smoothness or sparsity). Our work contributes in several main ways. First, we study a two-stage doubly robust CATE estimator and give a generic model-free error bound, which, despite its generality, yields sharper results than those in the current literature. We apply the bound to derive error rates in nonparametric models with smoothness or sparsity, and give sufficient conditions for oracle efficiency. Underlying our error bound is a general oracle inequality for regression with estimated or imputed outcomes, which is of independent interest; this is the second main contribution. The third contribution is aimed at understanding the fundamental statistical limits of CATE estimation. To that end, we propose and study a local polynomial adaptation of double-residual regression. We show that this estimator can be oracle efficient under even weaker conditions, if used with a specialized form of sample splitting and careful choices of tuning parameters. These are the weakest conditions currently found in the literature, and we conjecture that they are minimal in a minimax sense. We go on to give error bounds in the non-trivial regime where oracle rates cannot be achieved. Some finite-sample properties are explored with simulations.
David Benseker, PhD, MPH, Assistant Professor
Emory University Department of Biostatistics and Bioinformatics.
October 27, 2020
Abstract: One of the best hopes we have of returning life to normal is to bring a safe and effective preventive COVID-19 vaccine to market and make it available to just about everybody around the world. We are in the middle of an unprecedented effort to bring such a vaccine to market. After a recent pressure campaign led by academic scientists, vaccine developers have made public the protocols for their Phase III trials. The release of these protocols has ignited a fierce debate as to whether the designs are appropriate and sufficiently safe-guarded from political pressure for vaccine approval. In this talk I will discuss a few of the complex issues involved in designing Phase III COVID vaccine trials, touching on some key statistical aspects of the trials along the way.
Department of Mathematical and Statistical Sciences
University of Alberta
October 13, 2020
BIS Seminar: Dealing with observed and observed effect moderators wehn estimating population average treatment effects
Associate Dean for Education
Bloomberg PRofessor of American Health
September 22, 2020
Qingyuan Zhao, University of Cambridge
Biostatistics Seminar: BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Qingyuan Zhao, Statistical Laboratory, University of Cambridge
May 5, 2020
BIS Seminar - 6.23.2020 - Model-averaged estimation of molecular evolution and natural selection in SARS-COV-1 and SARS-CoV-2 coronaviruses during zoonosis
Jeffrey Townsend, PhD
Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology
Biostatistics Seminar - 6.9.2020
Frank Harrel, Professor of Biostatistics
Vanderbilt University School of Medicine
Associate Professor of Biostatistics, Statistics & Data Science, Operation, and Ecology & Evolutionary Biology
5.25.2020 Biostatistics Seminar
Dan Weinberger, PhD, associate professor of Epidemiology (Microbial Diseases), Yale School of Public Health April 2020 Seminar