Gayface, Michael Clayton, and p-values

and some other things too

Recently in the blog:

• Close Reading Archive

• “I work in a biology lab . . . My PI proposed a statistical test that I think is nonsense. . .”

• “Of course, this could conceivably be a case of near unbelievable luck: A flawed analysis based on wrong assumptions gave an unusually large causal effect estimate – but the misguided result just happened to be correct. We can imagine how the research team huddled nervously around the computer terminal biting their nails and silently praying as they executed their updated Stata code, only to erupt in joy and celebration as the results appeared on screen and revealed they were right all along. . . .”

• New Course: Prediction for (Individualized) Decision-making

• Gayface Data Replicability Problems

• Michael Clayton in NYC

• Hey, journalist readers! Does anyone have a contact at NPR?

• Credit where due to NPR regarding science data fraud, and here’s how they can do even better

• 4 different meanings of p-value (and how my thinking has changed)

• Toward a unified theory of bad science and bad scholarship

Have a good week. As always, you can leave comments on the original posts.