Author: Bob C-J
I'm a teacher, researcher, and gadfly of neuroscience. My research interests are in the neural basis of learning and memory, the history of neuroscience, computational neuroscience, bibliometrics, and the philosophy of science. I teach courses in neuroscience, statistics, research methods, learning and memory, and happiness. In my spare time I'm usually tinkering with computers, writing programs, or playing ice hockey.

Open Statistics Conference – Talk and Resources

I had the great pleasure today of discussing the estimation approach (New Statistics) at the Open Statistics / Open Eyes conference in Cesena, University of Bologna. Here I’m posting some resources for those looking to get started with the New

Registered Reports: Conjuring Up a Dangerous Experiment

Last week I (Bob) had my first Registered Report proposal accepted at eNeuro. It’s another collaboration with my wife, Irina, where we will test two popular models of forgetting. The proposal, pre-registration, analysis script, and preliminary data are all on

Transparency of reporting sort of saves the day…

I’m in the midst of an unhappy experience serving as a peer reviewer. The situation is still evolving but I thought I’d put up a short post describing (in general terms) what’s happened because I’d be happy to have some

eNeuro’s new push to encourage estimation

eNeuro, one of the two journals published by the Society for Neuroscience, has revised its author guidelines to encourage estimation. That’s great news. Here is: The announcement and comment from editor Christophe Bernard An accompanying commentary from us that explains

The Cookie-Monster Study: The highly influential memory of a long-lost study

In psychology, there are a few studies so famous and influential that they have proper names: The Good Samaritan Study, the Asch Obedience Study, the Marshmallow test, etc, etc. Approaching this echelon is the “Cookie Monster Study”, an increasingly-famous study

Reply to Lakens: The correctly-used p value needs an effect size and CI

Updated 5/21: fixed a typo, added a section on when p > .05 demonstrates a negligible effect, and added a figure at the end. Daniel Lakens recently posted a pre-print with a rousing defense of the much-maligned p-value: In essence, the

Microworlds

Last month I (Bob) visited a local elementary school for a “Science Alliance” visit. This is a program in our community to being local scientists into the classroom. I brought the Cartoon Network simulator I have been developing (Calin-Jageman, 2017,

Joining the fractious debate over how to do science best

At the end of the month (March 2019) the American Statistical Association will publish a special issue on statistical inference “after p values”. The goal of the issue is to focus on the statistical “dos” rather than statistical “don’ts”. Across

Sizing up behavioral neuroscience – a meta-analysis of the fear-conditioning literature

Inadequate sample sizes are kryptonite to good science–they produce waste, spurious results, and inflated effect sizes.  Doing science with an inadequate sample is worse than doing nothing.  In the neurosciences, large-scale surveys of the literature show that inadequate sample sizes

Positive Controls for Psychology – My pitch for a SIPS project

Positive controls are one of the most useful tools for ensuring interpretable and fruitful research.  Strangely, though, positive controls are rarely used in psychological research.  That’s a shame, but also an opportunity–it would be an easy but substantial improvement for

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