We develop two strategic statistical models of the principal-agent game and discuss how to use them to distinguish among substantive explanations for deviations from subgame-perfection. [Working paper]

Applies a strategic statistical model to the gathered lab data to explain overly generous offers and mysterious rejections. [Working paper]

Develops a strategic statistical model of the ultimatum game and presents experimental evidence as to the nature of uncertainty in these games. Presented: PolMeth 2008, APSA 2008, SPSA 2009. [Under review]

Network analysis is flourishing, but theories explaining why networks take the form they do are still in the early stages of development. I am developing a network game to explain how justices choose cases to cite, where utility for opinion authors takes the form of a new empirical measure of node importance. Presented: 2009 Midwest. [Working paper]

Sometimes I edit R files in a shell using the great, simple text file editor GNU nano. If you do, you will want to add syntax highlighting support for R to nano. This is easy: add a few lines to your ~/.nanorc file and nano will do the rest.

Here are the lines I use:

Tools to plot descriptive statistics, posterior distributions, and more. Includes linePlotModels, descripBarplot, and other functions I've found useful.

The strategic character of abstentions makes the assumption of ignorability difficult to meet in practice. We discuss different abstention-generating mechanisms to understand the conditions under which they may be deemed ignorable, and extend the MCMC IRT model so as to incorporate information from abstention patterns into inferences about legislators' ideal points. With Guillermo Rosas and Yael Shomer. [In progress]

In collaboration with Randall Calvert. We develop a model of political communication prior to the play of a coordination game and use it to examine the process by which political messages acquire meaning. Presented: Midwest 2007. [Working paper]

In collaboration with Jeff Gill, John Freeman, and Aaron Rapport. We are developing a browser-based software system, Elicit, for eliciting structured information about social networks for updating Bayesian models of connectivity. [In progress]