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

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Researchers have used contorted, inefficient, and arbitrary analyses to demonstrated added value in biomarkers, genes, and new lab measurements. Traditional statistical measures have always been up to the task, and are more powerful and more flexible. It’s time to revisit them, and to add a few slight twists to make them more helpful.

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The performance metrics chosen for prediction tools, and for Machine Learning in particular, have significant implications for health care and a penetrating understanding of the AUROC will lead to better methods, greater ML value, and ultimately, benefit patients.

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

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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.

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

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Publications

2018

Recent & Upcoming Talks

Musings on Statistical Models vs. Machine Learning in Health Research
Sep 18, 2018 12:00 PM
Regression Modeling Strategies
Aug 2, 2018 12:00 PM
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
Current Challenges and Opportunities in Clinical Prediction Modeling
Jul 2, 2018 12:00 AM
Using R, Rmarkdown, RStudio, knitr, plotly, and HTML for the Next Generation of Reproducible Statistical Reports
Nov 16, 2017 12:00 AM

Projects

FDA Office of Biostatistics

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

Teaching

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.

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