Accounting for Bias and Confounding

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Description

Bias and confounding, if not managed effectively, can impact the validity of your research findings.

In this module, you will learn a range of strategies to minimize bias and to control for confounding.

By the end of this module, you will be able to:

  • Define exposure, outcome, and association
  • Distinguish between selection bias, information bias, and confounding
  • Explain the issues that these factors pose for data collection and/or interpretation
  • Identify strategies for dealing with data collection and interpretation challenges

Gretchen White, PhD
Assistant Professor of Medicine, Epidemiology, and Clinical and Translational Science
University of Pittsburgh

Dr. White’s research spans topics of alcohol use, substance use, bariatric surgery outcomes, obesity, and workforce development. She has collaborated on multiple observational studies and clinical trials. Dr. White teaches Scientific Writing and Presentation Skills, Best Practices in Clinical Research, Advanced Observational Methods, and Clinical Research Methods. She also mentors graduate, postdoctoral, and early-career investigators. Dr. White has published over 50 peer-reviewed articles in well-respected, high-impact journals.

Learn how to draft a clinical research question and proposal, identify a range of study designs for observational and interventional studies, and control for bias and confounding.

Modules in this Stack are case-based, interactive, and entirely self-paced, combining convenience and flexibility with deep, engaged learning. Take them all to earn a competency-based certificate.

Other modules in this Stack:

  • Introducing Clinical Research
  • Accounting for Bias and Confounding
  • Crafting a Clinical Research Question and Proposal
  • Experimental Studies in Clinical Research
  • Observational Studies in Clinical Research

Module Content