Category: NHST

Pre-Print – The New Statistics for Better Science

We have a new preprint on how the New Statistics can save the world (sort of):  It’s for a special issue of the American Statistician on the them of  “Beyond p values”. We welcome your feedback on via email, twitter (@TheNewStats),

Banning p values? The journal ‘Political Analysis’ does it

Back in the 1980s, epidemiologist Kenneth Rothman was a leader of those trying to persuade researchers across medicine and the biosciences to use CIs routinely. The campaign was successful to the extent that the International Council of Medical Editors stated

Statisticians see the light–Hooray!

“Scientific Method for the Twenty-First Century: A World Beyond p

Video – Getting started with the New Statistics and Open Science

This fall I (Bob) was invited to give a talk at Indiana University as part of a series on good science and statistical practice organized by the university’s Social Science Research Commons (SSRC).  The SSRC is like a core facility

The ASA Symposium on Statistical Inference: Bob’s great talk

“A world beyond p < .05." That's the subtitle for the ASA Symposium on Statistical Inference, which ran last month. Bob was there and recently posted a brief initial report. I wasn’t there, alas, but I’ve now had three independent

Adventures in Replication – Reviewers don’t want to believe disappointing replication results

Trying to publish replication results is difficult.  Even when the original evidence is very weak or uncertain, reviewers tend to look for reasons to explain away a smaller effect in the replication.  If nothing comes to mind, reviewers may even

Beyond p values – Dispatches from the ASA symposium on statistical inference

The next couple of posts will be about my experience at the ASA conference on statistical inference: A World Beyond p < .05. The first session featured Steve Goodman and John Ioannidis (who Skyped in from Australia).  One highlight was

Adventures in Replication: p values and Illusions of Incompatibility

Here’s an idea I run into a lot in peer reviews of replication studies: If the original study found p < .05 but the replication found p > .05, then the results are incompatible and additional research is needed to

p values and outrageous results

If you were researching a muscle-building supplement and read that a test of the supplement produced an increase in muscle mass by 200% within a month, you’d be right to be skeptical.  Perhaps randomization had broken down, perhaps there was

Danny Kahneman: From p values to Nobel Prize

You meet a red-headed person who is a bit short-tempered then, later, another who is similarly touchy. You start to believe that red hair signals ‘watch out’. Really? You are leaping to a conclusion from an extremely small sample! But