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…

Apr 30, 2026
Questions We Forget To Ask When Designing an RCT

Randomized clinical trial designs tend to be traditional, and there is a lot of inertia working against the use of modern designs. There are also a lot of futile RCTs, many…

Apr 16, 2026
Goal-Driven Flexible Bayesian Design

The majority of clinicals trials that are successfully launched end with equivocal results, with confidence intervals that are too wide to allow drawing a conclusion other…

Sep 17, 2025
Bayesian Thinking

This presentation covers Bayesian thinking and how different it is from frequentist thinking, with a variety of examples. Unique advantages of Bayesian thinking are…

Jan 27, 2025
Ordinal State Transition Models as a Unifying Risk Prediction Framework

In this talk I will present a case for the use of discrete time Markov ordinal longitudinal state transition models as a unifying approach to modeling a variety of outcomes…

Nov 18, 2024
Tips for Biostatisticians Collaborating with Non-Biostatistician Medical Researchers

In this talk I contrast consultation with collaboration and discuss various ways to make collaborations most effective. Some key components of effective collaboration are…

Jul 30, 2024
Rare Degenerative Diseases & Statistics:
Methods for Analyzing Composite Patient Outcomes

In this talk I’ll explain why statistical power is maximized by analyzing the rawest form of clinical trial outcome data, as opposed to analyzing patients at a single time…

Jul 11, 2024
Overview of Composite Outcome Scales & Statistical Approaches for Analyzing Them

There are many issues surrounding the choice and construction of clinical outcome scales for randomized clinical trials, and several analytical methods from which to choose.…

Jan 30, 2024
My Big Jump: Founding a Department of Biostatistics

For many years biostatistics had been successful at Vanderbilt, but the opportunity to create a department home for biostatistics was too good to pass up. The new department…

Mar 20, 2023
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
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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