By Chris Fariss
I found the following post at Chris Blattman‘s blog; however, the original post is from yet another blog, The Frontal Cortex. Is this cross-blogging or blog-crossing? Anyway, I think the experiments will be of interest to our group. Enjoy.
For the most part, self-control is seen as an individual trait, a measure of personal discipline. If you lack self-control, then it’s your own fault, a character flaw built into the brain.
However, according to a new study by Michelle vanDellen, a psychologist at the University of Georgia, self-control contains a large social component; the ability to resist temptation is contagious. The paper consists of five clever studies, each of which demonstrates the influence of our peer group on our self-control decisions.
For instance, in one study 71 undergraduates watched a stranger exert self-control by choosing a carrot instead of a cookie, while others watched people eat the cookie instead of the carrot. That’s all that happened: the volunteers had no other interaction with the eaters. Nevertheless, the performance of the subjects was significantly altered on a subsequent test of self-control. People who watched the carrot-eaters had more discipline than those who watched the cookie-eaters.
Be sure to check out the many other interesting posts at Chris Blattman‘s blog. As for The Frontal Cortex, this was my first visit to the site but it might be worth exploring a bit more.
By Chris Fariss
Keith Schnakenberg and I are working on a paper in which we measure the unobservable level of respect for human rights. We use the same Bayesian model that Shawn Treier and Simon Jackman use to measure the latent level of democracy in their 2008 paper that was published in the American Journal of Political Science. As with the construction of GRE scores, the ordinal item-response (IRT) model explicitly models the measurement error that results when different component indicators are aggregated together.
Posterior densities for item discrimination parameters for individual physical integrity rights (300 draws). The item discrimination parameter represent the degree to which the item discriminates between states' along the latent human rights variable. Greater values along the x-axis signify greater discrimination by the item.
The data we use to estimate the IRT model is available from the CIRI Human Rights Data Project. The model allows us to generate point estimates and credible intervals for the latent variable of interest.
Latent variables estimates for all 192 countries in the CIRI dataset in the year 2007. Blue dots are point estimates (posterior means) and red lines are 95% credible intervals.
For those interested, Simon Jackman has posted several slide-shows on his website that demonstrate the IRT model in action. In our paper we also demonstrate a simple way to include the uncertainty from the estimates in models that include such a measure as an independent variable. You can download a copy of our paper at SSRN (we will upload the paper soon). For now, here is the current version of our abstract:
By Jason J. Jones
Five journalists have volunteered to be locked in a house with no access to the outside world except Facebook and Twitter. Their task will be to report the day’s news as best they can using only these sources.
The Washington Post and Ars Technica are optimistic. Personally, I wouldn’t be surprised if the stories they report end up a little garbled.