Statistical Thinking

This blog is devoted to statistical thinking and its impact on science and everyday life. Emphasis is given to maximizing the use of information, avoiding statistical pitfalls, describing problems caused by the frequentist approach to statistical inference, describing advantages of Bayesian and likelihood methods, and discussing intended and unintended differences between statistics and data science. I’ll also cover regression modeling strategies, clinical trials, drug evaluation, medical diagnosis, and decision making.

Recent Posts

More Posts

This article lays out the rationale and overall design of a new discussion site about quantitative methods.


This article provides my reflections after the PCORI/PACE Evidence and the Individual Patient meeting on 2018-05-31. The discussion includes a high-level view of heterogeneity of treatment effect in optimizing treatment for individual patients.


This article elaborates on Frank Harrell’s post providing guidance in choosing between machine learning and statistical modeling for a prediction project.


This article provides general guidance to help researchers choose between machine learning and statistical modeling for a prediction project.


This article discusses issues related to alpha spending, effect sizes used in power calculations, multiple endpoints in RCTs, and endpoint labeling. Changes in endpoint priority is addressed. Included in the the discussion is how Bayesian probabilities more naturally allow one to answer multiple questions without all-too-arbitrary designations of endpoints as “primary” and “secondary”. And we should not quit trying to learn.




Recent & Upcoming Talks

Simple Bootstrap and Simulation Approaches to Quantifying Reliability of High-Dimensional Feature Selection
Jul 31, 2018 10:35 AM
Regression Modeling Strategies
Jul 29, 2018 8:30 AM


FDA Office of Biostatistics

Enhancing capabilities of CDER and its Office of Biostatistics in Bayesian clinical trial design and analysis


I teach the BIOS7330 Regression Modeling Strategies course in the Biostatistics Graduate Program at Vanderbilt University in the spring semester. The course web page is here. I teach a 4-day version of this course each May at Vanderbilt. Registration information for the short course may be found here.