[This is the first of a two-part series motivating and introducing precis, a Python package for automated abbreviation of psychometric measures. In part I, I motivate the search for shorter measures by arguing that internal consistency is highly overrated. In part II, I describe some software that makes it relatively easy to act on this … Continue reading Internal consistency is overrated, or How I learned to stop worrying and love shorter measures, Part I
TL;DR: I wrote a minimalistic state machine implementation in Python. You can find the code on GitHub. The rest of this post explains what a state machine is and why you might (or might not) care. The post is slanted towards scientists who are technically inclined but lack formal training in computer science or software … Continue reading yet another Python state machine (and why you might care)
If you’ve visited the Neurosynth website lately, you may have noticed that it looks… the same way it’s always looked. It hasn’t really changed in the last ~20 months, despite the vague promise on the front page that in the next few months, we’re going to do X, Y, Z to improve the functionality. The … Continue reading the Neurosynth viewer goes modular and open source
Many (most?) regular readers of this blog have probably been to at least one academic conference. Some of you even have the misfortune of attending conferences regularly. And a still-smaller fraction of you scholarly deviants might conceivably even enjoy the freakish experience. You know, that whole thing where you get to roam around the streets … Continue reading unconference in Leipzig! no bathroom breaks!
Warning: what follows is a somewhat technical discussion of my love-hate relationship with the R statistical language, in which I somehow manage to waste 2,400 words talking about a single line of code. Reader discretion is advised. I’ve been using R to do most of my statistical analysis for about 7 or 8 years now–ever … Continue reading R, the master troll of statistical languages
Over the past couple of months, I’ve been working on and off on a collaboration with my good friend Nick Holtzman and some other folks that focuses on ways to automatically extract bias from text using a vector space model. The paper is still in progress, so I won’t give much away here, except to … Continue reading estimating bias in text with Ruby
After the CNS symposium on building a cumulative cognitive neuroscience, several people I talked to said it was a pity there wasn’t an online repository where all the sites that the speakers discussed could be accessed. I should have thought of that ahead of time, because even if we made one now, no one would … Continue reading links and slides from the CNS symposium
A while back I blogged about a paper I wrote that uses genetic algorithms to abbreviate personality measures with minimal human intervention. In the paper, I promised to put the R code I used online, so that other people could download and use it. I put off doing that for a long time, because the … Continue reading abbreviating personality measures in R: a tutorial
Drew Conway has a great list of 10 must-have R packages for social scientists. If you’re a social scientist (or really, any kind of scientist) who doesn’t use R, now is a great time to dive in and learn; there are tons of tutorials and guides out there (my favorite is Quick-R, which is incredibly … Continue reading got R? get social science for R!