Once a month during the academic year, the statistics faculty select a paper for our students to read and discuss. Papers are selected based on their impact or historical value, or because they contain useful techniques or results.
Benjamini, Y. (2020). Selective Inference: The Silent Killer of Replicability. Harvard Data Science Review, 2(4).
Notes preparer: Elizabeth Schifano
Following the recent attack on statistical testing and p-values in the quest for replicability, Yoav Benjamini was one of several statisticians to come forward in defense of the p-value. He argues the problem of replicability is instead likely rooted in selective inference: “Selective inference is focusing statistical inference on some findings that turned out to be of interest only after viewing the data. Without taking into consideration how selection affects the inference, the usual statistical guarantees offered by all statistical methods deteriorate.”
We will discuss the crisis of replicability, and how p-values and selective inference are involved in this crisis.