Month: April 2017

Don’t fool yourself: Facilitated Communication continues to be a cautionary tail

When I (Bob) was an undergrad, I took methods/stats in the psychology department.  I wasn’t a psych major, but I wanted to take a class on brain and behavior, and I was told I had to take methods/stats first.  At

Posted in Uncategorized

The persistence of NHST: “Wilfully stupid”?

I recently gave a research talk to Psychology at La Trobe, my old University–although I now live an hour out of the city and rarely visit the campus. I decided to turn things around from my previous few talks: Instead

Posted in NHST, Replication, The New Statistics

Castles made of sand in the land of cancer research

Not all problems with scientific practice are statistical.  Sometimes, methods and protocols are introduced and accepted without sufficient vetting and quality control.  Hopefully this is rare, but in the biological sciences there is an ongoing worry that too many ‘accepted’

Posted in Replication

p intervals: Replicate and p is likely to be *very* different!

The Significance Roulette videos (here and here) are based on the probability distribution of the p value, in various situations. There’s more to the second video than I mentioned in my recent post about it. The video pictures the distribution of replication

Posted in NHST, Replication

Significance Roulette 2

In my post of a couple of days ago I gave the link to Significance Roulette 1, a video that explains how to generate the roulette wheel for a ‘typical experiment’, by which I meant an independent groups experiment, N = 32

Posted in ITNS, NHST, Replication, The New Statistics

Significance Roulette 1

If you run an experiment, obtain p = .05, then repeat the experiment–exactly the same but with a new sample–what p value are you likely to get? The answer, surprisingly, is just about any value! In other words, the sampling

Posted in ITNS, NHST, Replication, The New Statistics

The long road towards clinical trials registries – Sackler Colloquim on Reproducibility Field Report 4

Science only works if we have the whole story. This is especially important in clinical trials, where the results of these studies are used to guide medical practice.  Unfortunately, getting the whole story can be difficult–there are strong incentives to

Posted in Uncategorized

Replication is the new black, and not only in Psychology: Economics too

There are good folks in many disciplines who are working to encourage Open Science practices. Here’s an example from economics: A website that promotes replication. The Network is run by Bob Reed, at the University of Canterbury in New Zealand

Posted in Open Science, Replication

A conference about–wait for it–the p value! But other things too.

In March 2016 the American Statistical Association (ASA) posted online a policy statement about the p value. You can see it here. This was remarkable–for one thing because it was the first time the ASA had made a public pronouncement

Posted in NHST, Open Science, The New Statistics

Science Spin – Sackler Colloquim on Reproducibility Field Report 3

The conference on reproducibility I (Bob) attended in early March was so invigorating I figured I would spread these posts out.  Here’s the next installment. Another good talk on the first day was from Isabelle Boutron, an MD PhD at

Posted in Uncategorized