Improving Your Science: Sample-Size Planning, Pre-Registration, and Reproducible Data Analysis
- Featured in:
- SfN Annual Meeting Recordings
Mar 14, 2018
This workshop introduces three emerging best practices to improve the rigor and reproducibility of neuroscience research:
- Sample-size planning.
- Pre-registration.
- The Teaching Integrity in Empirical Research (TIER) Protocol for conducting reproducible data analysis.
Each discussion provides a 30-minute overview of the topic and include resources and tips for advancing towards mastery.
Speakers
Robert Calin-Jageman, PhD
Robert Calin-Jageman, PhD, is a professor of psychology and neuroscience program director at Dominican University. He received his bachelor's degree in philosophy from Albion College, a PhD in physiological psychology from Wayne State University, and his postdoctoral fellowship in neurobiology at Georgia State University in the lab of Paul S. Katz. Calin-Jageman's research lab studies the neurobiology of learning and memory, using sensitization in Aplysia as our model system. He also develops open-source tools for statistical analysis and neuroscience education.
David Mellor, PhD
David Mellor is a project manager at the Center for Open Science (COS), where he leads the incentives program. He works with researchers, editors, and developers to increase transparency and reproducibility in science. His research interests cover the behavioral ecology of cichlid fish, citizen science, and undergraduate student retention. Mellor earned his BS in biology from the College of William and Mary and his PhD in ecology and evolution from Rutgers University.
Richard Ball, PhD
Richard Ball is professor of economics at Haverford College and a co-founder and co-director of Project Teaching Integrity in Empirical Research (TIER), an initiative that develops protocols and curriculum to promote transparency and reproducibility in empirical research. Ball’s primary teaching areas are game theory and statistical methods. He earned his BA in anthropology and African studies from Williams College, MS in agricultural economics from Michigan State University, and his PhD in agricultural and resource economics from the University of California, Berkeley.
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