The Replication Network
Furthering the Practice of Replication in Economics
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Don’t Abandon It! Learn (and Teach) to Use It Correctly
[From the paper “The practical alternative to the p-value is the correctly used p-value” by Daniël Lakens, posted at PsyArXiv Preprints] “I do not think it is useful to tell researchers what they want to know. Instead, we should teach…
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 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 MoreHow do Psychologists Interpret Nonsignificant Results? Evidence from the Journals
[From the abstract to the article, “Quantifying Support for the Null Hypothesis in Psychology: An Empirical Investigation” by Aczel et al., recently published in Advances in Methods and Practices in Psychological Science] “In the traditional statistical framework, nonsignificant results leave researchers…
Read MoreGELMAN: Some Natural Solutions to the p-Value Communication Problem—And Why They Won’t Work
[NOTE: This is a repost of a blog that Andrew Gelman wrote for the blogsite Statistical Modeling, Causal Inference, and Social Science]. Blake McShane and David Gal recently wrote two articles (“Blinding us to the obvious? The effect of statistical…
Read MoreBayes Factors Versus p-Values
In a recent article in PLOS One, Don van Ravenzwaaij and John Ioannidis argue that Bayes factors should be preferred to significance testing (p-values) when assessing the effectiveness of new drugs. At his blogsite The 20% Statistician, Daniel Lakens argues…
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