The Replication Network
Furthering the Practice of Replication in Economics
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How Pre-Registration Can Lead to Higher-Powered Studies and Increase Reproducibility
[From the paper “Preregistration and reproducibility” by Eirik Strømland, forthcoming in the Journal of Economic Psychology] “I present a simple model in which the research community is populated by agents who may report their results unconditionally or conditionally on statistical…
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 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 MoreHow to Get Something from Nothing. Or, “Yes, Virginia, You Can Do Ex-post Power Analyses”.
[From the article, “The effect of the conservation reserve program on rural economies: Deriving a statistical verdict from a null finding” by Jason Brown, Dayton Lambert, and Timothy Wojan, recently published in the American Journal of Agricultural Economics] “This article suggests…
Read MoreThe Truth is Out There. It’s Just Not Very Likely.
[From the paper, “Perceived Crisis and Reforms: Issues, Explanations, and Remedies”, authored by Paul De Boeck and Minjeong Jeon, published in the July issue of Psychological Bulletin] “…we believe that the OSC [Open Science Collaboration] study allows us to obtain…
Read MoreCOVILLE & VIVALT: Should We Trust Evidence On Development Programs?
[From the working paper, “How Often Should We Believe Positive Results? Assessing the Credibility of Research Findings in Development Economics” by Aidan Coville and Eva Vivalt] Over $140 billion is spent on donor assistance to developing countries annually to promote…
Read MoreREED: Post-Hoc Power Analyses: Good for Nothing?
Observed power (or post-hoc power) is the statistical power of the test you have performed, based on the effect size estimate from your data. Statistical power is the probability of finding a statistical difference from 0 in your test (aka…
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