Controversies in Predictive Modeling, Machine Learning, and Validation
This talk covers a variety of controversial and/or current issues related to statistical modeling and prediction research. Some of the topics covered are why external…
Sep 28, 2022
R Workflow for Reproducible Biomedical Research Using Quarto
This work is intended to foster best practices in reproducible data documentation and manipulation, statistical analysis, graphics, and reporting. It will enable the reader…
Sep 26, 2022
Longitudinal Ordinal Models as a General Framework for Medical Outcomes
Univariate ordinal models can be used to model a wide variety of longitudinal outcomes, using only standard software, through the use of Markov processes. This talk will…
Dec 18, 2021
Modernizing Clinical Trial Design and Analysis to Improve Efficiency & Flexibility
This presentation covers several ways to make clinical trials more efficient and to reduce the chance of ending with an equivocal result. Some of the approaches covered are…
Nov 4, 2021
Musings on Statistical Models vs. Machine Learning in Health Research
Health researchers and practicing clinicians are with increasing frequency hearing about machine learning (ML) and artificial intelligence applications. They, along with…
Jun 9, 2021
Sequential Bayesian Designs for Rapid Learning in COVID-19 Clinical Trials
Continuous learning from data and computation of probabilities that are directly applicable to decision making in the face of uncertainty are hallmarks of the Bayesian…
Nov 25, 2020
Controlling α vs. Probability of a Decision Error
This presentation clarifies what type I assertion probability α protects against, by making a clear distinction between how often we assert an effect vs. how often we are…
Nov 13, 2020
Bayes for Flexibility in Urgent Times
Continuous learning from data and computation of probabilities that are directly applicable to decision making in the face of uncertainty are hallmarks of the Bayesian…
Jul 1, 2020
Fundamental Advantages of Bayes in Drug Development
This presentation covers the limitations of frequentist inference for answering clinical questions and generating evidence for efficacy. Key to understanding efficacy is…
Apr 27, 2020
Casual Inference Podcast
This interview by Ellie Murray and Lucy D’Agostino McGowan for their Casual Inference podcast recorded 2020-02-26 is titled Getting Bayesian
Apr 23, 2020
R for Graphical Clinical Trial Reporting
For clinical trials a good deal of effort goes into producing both final trial reports and interim reports for data monitoring committees, and experience has shown that…
Jan 29, 2020
Why Bayes for Clinical Trials?
This presentation covers the limitations of frequentist inference for answering clinical questions and generating evidence for efficacy. Key to understanding efficacy is…
Sep 20, 2019
R for Clinical Trial Reporting
Statisticians and statistical programmers spend a great deal of time analyzing data and producing reports for clinical trials, both for final trial reports and for interim…
Sep 13, 2019
Bayesian Thinking Podcast
This interview by Vinay Prasad for his Plenary Session podcast discusses Bayesian thinking, especially about clinical trials.
Aug 7, 2019
Regression Modeling Strategies
Short course
May 3, 2019
Simple Bootstrap and Simulation Approaches to Quantifying Reliability of High-Dimensional Feature Selection
Feature selection in the large p non-large n case is known to be unreliable, but most biomedical researchers are not aware of the magnitude of the problem. They assume for…
Jul 31, 2018
Current Challenges and Opportunities in Clinical Prediction Modeling
This talk covers a variety of topics in clinical prediction modeling, with emphasis on quantifying the added value of new predictors.
Jul 4, 2018
Using R, Rmarkdown, RStudio, knitr, plotly, and HTML for the Next Generation of Reproducible Statistical Reports
The Vanderbilt Department of Biostatistics has two policies currently in effect:
1. All statistical reports will be reproducible
2. All reports should include all the…
Nov 16, 2017
Exploratory Analysis of Clinical Safety Data to Detect Safety Signals
It is difficult to design a clinical study to provide sound inferences about safety effects of drugs in addition to providing trustworthy evidence for efficacy. Patient…
Jun 8, 2006
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