Published Jan 22, 2018

John Ioannidis on Statistical Significance, Economics, and Replication

Renowned researcher John Ioannidis delves into the pitfalls of statistical significance, the replication crisis in economics, and the urgent need for preregistration and well-powered studies, advocating for enhanced transparency and scientific rigor in research methodologies.

Episode Highlights

Topics covered

Episode Highlights

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John Ioannidis on Statistical Significance, Economics, and Replication

Topics covered

Popular Clips

The Winner's Curse

Observational Studies: Reliability and Limitations

Uncovering Bias

Statistical Significance and Plausible Effect Sizes

Understanding Statistical Significance

Replication Crisis in Economics

The Multiplicity Burden

The Uncertainty of Science

Improving Scientific Research

Improving Research Methods

The Impact of Minimum Wage

Statistical Significance

Science and Skepticism

Metaanalysis in Science

Episode Highlights

Research Methodology

Bias in Science

Statistical Significance

Related Episodes

Ed Yong on Science, Replication, and Journalism

James Heckman on Facts, Evidence, and the State of Econometrics

John Cochrane on the Financial Crisis

Brian Nosek on Truth, Science, and Academic Incentives

Brian Nosek on the Reproducibility Project

Andrew Gelman on Social Science, Small Samples, and the Garden of the Forking Paths

Robin Hanson on Signalling

Ian Ayres on Super Crunchers and the Power of Data

Steven Levitt on Freakonomics and the State of Economics

John Cochrane on the Pandemic

Dan Klein on Truth, Bias, and Disagreement

An Interview with Gary Becker

Joshua Angrist on Econometrics and Causation

John Cochrane on Economic Growth and Changing the Policy Debate

Susan Athey on Machine Learning, Big Data, and Causation

John Ioannidis on Statistical Significance, Economics, and Replication

Topics covered

Popular Clips

Episode Highlights

Research MethodologyJohn Ioannidis examines the limitations of observational studies and the role of meta-analysis in research. He advocates for preregistration to enhance transparency and reduce biases in scientific studies.

Research Methodology

Bias in Science

Statistical SignificanceJohn Ioannidis explores the complexities of statistical significance and its implications for research reliability. He discusses the challenges of small sample sizes, the need for improved methodologies, and the importance of study power in effect size estimation.

Statistical Significance

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