The Replication Network
Furthering the Practice of Replication in Economics
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IN THE NEWS: Undark (March 21, 2019)
[From the article “Stats Experts Plead: Just Say No to P-Hacking” by Dalmeet Singh Chawla, published in Undark] “For decades, researchers have used a statistical measure called the p-value — a widely-debated statistic that even scientists find difficult to define — that is…
Read MoreSpecial Issue of The American Statistician: “Statistical Inference in the 21st Century: A World Beyond p < 0.05”
[From the introductory editorial “Moving to a World Beyond ‘p < 0.05’” by Ronald Wasserstein, Allen Schirm and Nicole Lazar, published in The American Statistician] “Some of you exploring this special issue of The American Statistician might be wondering if…
Read MoreHIRSCHAUER et al.: Twenty Steps Towards an Adequate Inferential Interpretation of p-Values in Econometrics
This blog is based on the homonymous paper by Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, and Claudia Becker in the Journal of Economics and Statistics. It is motivated by prevalent inferential errors and the intensifying debate on p-values – as…
Read MoreTo p-Value or Not to p-Value? An Answer From Signal Detection Theory
[From the article “Insights into Criteria for Statistical Significance from Signal Detection Analysis” by Jessica Witt, published in Meta-Psychology] “… the best criteria for statistical significance are ones that maximize discriminability between real and null effects, not just those that…
Read MoreWhen Trying to Explain p-Values, Maybe Try This?
[From the blog “P-values 101: An attempt at an intuitive but mathematically correct explanation” by Xenia Schmalz, posted at Xenia Schmalz’s blog] “…what exactly are p-values, what is p-hacking, and what does all of that have to do with the replication crisis?…
Read MoreHow Many Ways Can You Misinterpret p-Values, Confidence Intervals, Statistical Tests, and Power? 25
[From the blog “Misinterpreting Tests, P-Values, Confidence Intervals & Power” by Dave Giles, posted at his blogsite, Econometrics Beat] “Today I was reading a great paper by Greenland et al. (2016) that deals with some common misconceptions and misinterpretations that arise not…
Read MoreUsing Bayesian Reanalysis to Decide Which Studies to Replicate
[From the preprint “When and Why to Replicate: As Easy as 1, 2, 3?” by Sarahanne Field, Rink Hoekstra, Laura Bringmann, and Don van Ravenzwaaij, posted at PsyArXiv Preprints.] “…a flood of new replications of existing research have reached the…
Read MoreHIRSCHAUER et al.: Why replication is a nonsense exercise if we stick to dichotomous significance thinking and neglect the p-value’s sample-to-sample variability
[This blog is based on the paper “Pitfalls of significance testing and p-value variability: An econometrics perspective” by Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, and Claudia Becker, Statistics Surveys 12(2018): 136-172.] Replication studies are often regarded as the means to…
Read MoreFailure of Justice: p-Values and the Courts
[From the abstract of the working paper, “US Courts of Appeal cases frequently misinterpret p-values and statistical significance: An empirical study”, by Adrian Barnett and Steve Goodman, posted at Open Science Framework] “We examine how p-values and statistical significance have been interpreted…
Read More80% Power? Really?
[From the blog “The “80% power” lie” posted by Andrew Gelman in December 2017 at Statistical Modeling, Causal Inference, and Social Science] “Suppose we really were running studies with 80% power. In that case, the expected z-score is 2.8, and…
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