In my post on generating inverse probability weights for both binary and continuous treatments, I mentioned that I’d eventually need to figure out how to deal with more complex data structures and causal models where treatments, outcomes, and confounders vary over time.

My program evaluation class is basically a fun wrapper around topics in causal inference and econometrics. I’m a big fan of Judea Pearl-style “causal revolution” causal graphs (or DAGs), and they’ve made it easier for both me and my students to understand econometric approaches like diff-in-diff, regression discontinuity, and instrumental variables.

Why the filling of gaps in the research literature is similar to replication and probably better than its reputation.

Inspired by an email exchange I had with someone on theoretically non-exclusive hypotheses in Bayesian process tracing, I believed it might be useful to write down some thoughts in a blog post. It ended up as a PDF on Github because it has a minor R element and formal notation.

This is written for instructors in the Department of Public Management and Policy at the Andrew Young School of Policy Studies at Georgia State University, but it’s hopefully widely applicable too. With more than 100 universities moving their teaching online (including Emory just last night), it’s looking more and more inevitable that GSU will make a similar switch any time now.

Jessica Trounstine’s 2018 book Segregation by Design: Local Politics and Inequality in American Cities contributes to the public policy literature by exploring how segregation has affected local policy outcomes in the United States.

(See this notebook on GitHub) I’ve been teaching program evaluation in the MPA/MPP program at GSU for the past semester and a half, and since I was given free rein over how to teach it, I decided to make it as modern and cutting edge as possible.

See this notebook on GitHub. You can (and should) download the project from there if you want to follow along and try this out. tl;dr: Skip to the completed example. I use blogdown to generate the websites for all the courses I teach, and it’s delightful to not have to worry about databases and server configurations.

Now that I’m on the tenure track, I’ve been looking for a way to keep track of my different research projects so I can get them all finished and published. Matt Lebo’s “Managing Your Research Pipeline” presents a neat way of quantifying and tracking the progress of your research, and I recently adopted it for my own stuff. I even made a fancy R Markdown + flexdashboard dashboard to show the status of the pipeline interactively.

GSU uses Microsoft’s Office365 for e-mail, which is fine. My previous institutions—Duke and BYU—both use it too, and it’s pretty standard. GSU also enforces 2-factor authentication (2FA) with Duo, which is also fine. Everybody should use some sort of 2FA for all their important accounts! However, for whatever reason, GSU’s version of Duo’s 2FA doesn’t allow you to generate app-specific passwords for things like e-mail.