Archives


M Is For Pizza

[From the blog ““Tweeking”: The big problem is not where you think it is” by Andrew Gelman, posted at Statistical Modeling, Causal Inference, and Social Science] “In her recent article about pizzagate, Stephanie Lee included this hilarious email from Brian Wansink, the…

Read More

MCSHANE & GAL: Statistical Significance and Dichotomous Thinking Among Economists

[Note: This blog is based on our articles “Blinding Us to the Obvious? The Effect of Statistical Training on the Evaluation of Evidence” (Management Science, 2016) and “Statistical Significance and the Dichotomization of Evidence” (Journal of the American Statistical Association,…

Read More

A Roundtable Podcast on the Merits of Lowering the Threshold for Statistical Significance to 0.005

This past week, the International Methods Colloquium hosted a conference call on a recent proposal to reduce the threshold of statistical significance to 0.005.  Participants included Daniel Benjamin, Daniel Lakens, Blake McShane, Jennifer Tackett, E.J. Wagenmakers,  and Justin Esarey, all…

Read More

Is Fixing the Replication Crisis As Simple as Lowering the p-Value?

[From the article “A statistical fix for the replication crisis in science” by Valen E. Johnson at https://theconversation.com/au.] “In a trial of a new drug to cure cancer, 44 percent of 50 patients achieved remission after treatment. Without the drug, only…

Read More

Abandon Statistical Significance?

[From the abstract of a recent working paper by Blakeley McShane, David Gal, Andrew Gelman, Christian Robert, and Jennifer Tackett.] “In science publishing and many areas of research, the status quo is a lexicographic decision rule in which any result is first  required to have…

Read More

IN THE NEWS: Vox (July 31, 2017)

[From the article “What a nerdy debate about p-values shows about science — and how to fix it” by Brian Resnick at Vox.com]  “There’s a huge debate going on in social science right now. The question is simple, and strikes…

Read More

GELMAN: 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 More

ANDERSON & MAXWELL: There’s More than One Way to Conduct a Replication Study – Six, in Fact

NOTE: This entry is based on the article, “There’s More Than One Way to Conduct a Replication Study: Beyond Statistical Significance” (Psychological Methods, 2016, Vol, 21, No. 1, 1-12) Following a large-scale replication project in economics (Chang & Li, 2015)…

Read More

To p-value or Not To p-value, That Is The Question

[From the article, “Scientists, fishing for significance, get a meager catch” by Ivan Oransky and Adam Marcus at the website STAT] “If you cast a wide enough net, you’ll find what looks like a prize-winning fish. But you’ll also catch a…

Read More

The American Statistical Association Wants to Change the Way We Use p-values

[From an article at Retraction Watch] “After reading too many papers that either are not reproducible or contain statistical errors (or both), the American Statistical Association (ASA) has been roused to action. Today the group released six principles for the use…

Read More