I recently posted a guide (mostly for future-me) about how to analyze conjoint survey data with R. I explore two different estimands that social scientists are interested in—causal average marginal component effects (AMCEs) and descriptive marginal means—and show how to find them with R, with both frequentist and Bayesian approaches. However, that post is a little wrong. It’s not wrong wrong, but it is a bit oversimplified.

The students in my summer data visualization class are finishing up their final projects this week and I’ve been answering a bunch of questions on our class Slack. Often these are relatively standard reminders of how to tinker with specific ggplot layers (chaning the colors of a legend, adding line breaks in labels, etc.), but today one student had a fascinating and tricky question that led me down a realy fun dataviz rabbit hole.

In my research, I study international nongovernmental organizations (INGOs) and look at how lots of different institutional and organizational factors influence INGO behavior. For instance, many authoritarian regimes have passed anti-NGO laws and engaged in other forms of legal crackdown, which has forced NGOs to change their programming strategies and their sources of funding.

As I explained in my previous blog post, in June 2023 I drove my family across the country in a 5,000-mile roundtrip odyssey from Atlanta, Georgia to just-south-of-Salt Lake City, Utah, and back again.

In a couple days, I’m going to drive across the country to Utah, my home state. I haven’t been out west with my whole family in four years—not since 2019 when we moved from Spanish Fork, Utah to Atlanta, Georgia. According to Google Maps, it’s a mere 1,900 miles (3,000 kilometers) through the middle of the United States and should take 28 hours, assuming no stops.

I’ve been working on converting a couple of my dissertation chapters into standalone articles, so I’ve been revisiting and improving my older R code. As part of my dissertation work, I ran a global survey of international NGOs to see how they adjust their programs and strategies when working under authoritarian legal restrictions in dictatorship.

I’ve taught a course on data visualization with R since 2017, and it’s become one of my more popular classes, especially since it’s all available asynchronously online with hours of Creative Commons-licensed videos and materials.

In The Two Towers , while talking with Eowyn, Aragorn casually mentions that he’s actually 87 years old. When Aragorn is off running for miles and miles and fighting orcs and trolls and Uruk-hai and doing all his other Lord of the Rings adventures, he hardly behaves like a regular human 87-year-old. How old is he really?

Pandoc-flavored Markdown makes it really easy to cite and reference things. You can write something like this (assuming you use this references.bib BibTeX file): --- title: "Some title" bibliography: references.bib --- According to @Lovelace:1842, computers can calculate things.

My longstanding workflow for writing, citing, and PDF management When I started my first master’s degree program in 2008, I decided to stop using Word for all my academic writing and instead use plain text Markdown for everything. Markdown itself had been a thing for 4 years, and MultiMarkdown—a pandoc-like extension of Markdown that could handle BibTeX bibliographies—was brand new.