That’s the title of a paper accepted for publication in The American Statistician. (I confess that I added the “!”) The paper is here. Scroll down below to see the abstract. The paper boasts an interdisciplinary team of authors, including …
A week or two ago Simine Vazire was in town. Fiona Fidler organised a great Open Science jamboree to celebrate. The program is here and a few of the sets of slides are here. Simine on the credibility revolution First …
“The best thing about being a statistician is that you get to play in everyone’s backyard.” –a well-known quote from John Tukey. Cabbage? That’s CABG–see below. A week or so ago Lindy and I spent a very enjoyable 5 days …
Cabbage? Open Science and cardiothoracic surgery Read more »
A recent powerful blog post (see below) against internal meta-analysis prompts me to ask the question above. (Actually, Steve Lindsay prompted me to write this post; thanks Steve.) In ITNS we say, on p. 243: “To carry out a meta-analysis …
I’m in Sydney, the great Manly surf beach just over the road. It’s an easy ferry ride to the Opera House and city centre. Lindy and I started this trip up from Melbourne with a few days with a cousin, …
Eating Disorders Research: Open Science and The New Statistics Read more »
Years ago, Matthew Page was a student in the School of Psychological Science at La Trobe University (in Melbourne), working with Fiona Fidler and me. He somehow (!) became interested in research methods and practices, especially as related to meta-analysis. …
It’s not going to be a popular opinion, but I think MTurk has become a danger to sound psychological science. This breaks my heart. MTurk has helped transform my career for the better. Moreover, MTurk participants are amazing: they are …
The Perils of MTurk, Part 1: Fuel to the Publication Bias Fire? Read more »
[UPDATE: Thanks to twitter I came across this marvelous book(Jussim, 2012) that does a great job explaining the Pygmalion effect, the controversy around it, and the overall state of research on expectancy effects. I’ve amended parts of this post based on …
We’ve Been Here Before: The Replication Crisis over the Pygmalion Effect Read more »
This is a post about the Diamond Ratio (DR), a simple measure of the extent of heterogeneity in a meta-analysis. We introduced the DR in ITNS. But first, some background. Fixed Effect (FE) model for meta-analysis The diamond at the …
Measuring Heterogeneity in Meta-Analysis: The Diamond Ratio (DR) Read more »
Here’s a short talk I gave at the 2017 Society for Neuroscience meeting on sample size planning. The talk discusses: Why you should plan your sample sizes in advance What not to do (how some common approaches can lead you …