The Hidden Problem in Dermatology Research

And What We Can Do About It

2026
University of Louisville
CME
Bayesian Data Analysis
At the University of Louisville Division of Dermatology CME event, Dr. Miller presents an overview of how large analytic search spaces can introduce bias and distort inference in clinical research, with a focus on common pitfalls in dermatology studies.
Author

David M. Miller

Published

April 20, 2026

Event

University of Louisville Division of Dermatology Continuing Medical Education

Overview & Learning Objectives

By the end of this session, participants will be able to:

  • Describe what is meant by an analytic search space and how it arises in clinical research

  • Recognize common sources of bias related to multiplicity and selective reporting

  • Interpret p-values and statistical results within the context of analytic flexibility

  • Identify practical strategies (e.g., pre-registration, sensitivity analyses) to improve research rigor and transparency

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