This presentation covers Bayesian thinking and how different it is from frequentist thinking, with a variety of examples. Unique advantages of Bayesian thinking are…
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…
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…
In this talk I contrast consultation with collaboration and discuss various ways to make collaborations most effective. Some key components of effective collaboration are…
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…
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.…
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…
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…
This work is intended to foster best practices in reproducible data documentation and manipulation, statistical analysis, graphics, and reporting. It will enable the reader…
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…
Health researchers and practicing clinicians are with increasing frequency hearing about machine learning (ML) and artificial intelligence applications. They, along with…
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…
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…
This presentation covers the limitations of frequentist inference for answering clinical questions and generating evidence for efficacy. Key to understanding efficacy is…
This interview by Ellie Murray and Lucy D’Agostino McGowan for their Casual Inference podcast recorded 2020-02-26 is titled Getting Bayesian
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…
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…
This interview by Vinay Prasad for his Plenary Session podcast discusses Bayesian thinking, especially about clinical trials.
Short course
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…
This talk covers a variety of topics in clinical prediction modeling, with emphasis on quantifying the added value of new predictors.
The Vanderbilt Department of Biostatistics has two policies currently in effect:1. All statistical reports will be reproducible2. All reports should include all the…
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…
--- title: "" listing: - id: talk contents: "*/index.qmd" type: grid fields: [date, title, description] sort: "date desc" categories: cloud sort-ui: false filter-ui: false page-size: 12 page-layout: full title-block-banner: false toc: true --- ::: {#talks} :::