I’m moving to Austin!

The title pretty much says it. After spending four great years in Colorado, I’m happy to say that I’ll be moving to Austin at the end of the month. I’ll be joining the Department of Psychology at UT-Austin as a Research Associate, where I plan to continue dabbling in all things psychological and informatic, but … Continue reading I’m moving to Austin!

…and then there were two!

Last year when I launched my lab (which, full disclosure, is really just me, plus some of my friends who were kind enough to let me plaster their names and faces on my website), I decided to call it the Psychoinformatics Lab (or PILab for short and pretentious), because, well, why not. It seemed to … Continue reading …and then there were two!

bio-, chemo-, neuro-, eco-informatics… why no psycho-?

The latest issue of the APS Observer features a special section on methods. I contributed a pieceĀ discussing the need for a full-fledged discipline of psychoinformatics: Scientific progress depends on our ability to harness and apply modern information technology. Many advances in the biological and social sciences now emerge directly from advances in the large-scale acquisition, … Continue reading bio-, chemo-, neuro-, eco-informatics… why no psycho-?

tracking replication attempts in psychology–for real this time

I’ve written a few posts on this blog about how the development of better online infrastructure could help address and even solve many of the problems psychologists and other scientists face (e.g., the low reliability of peer review, the ‘fudge factor’ in statistical reporting, the sheer size of the scientific literature, etc.). Actually, that general … Continue reading tracking replication attempts in psychology–for real this time

Too much p = .048? Towards partial automation of scientific evaluation

Distinguishing good science from bad science isn’t an easy thing to do. One big problem is that what constitutes ‘good’ work is, to a large extent, subjective; I might love a paper you hate, or vice versa. Another problem is that science is a cumulative enterprise, and the value of each discovery is, in some … Continue reading Too much p = .048? Towards partial automation of scientific evaluation