I am a PhD candidate at the School of Communication at [The] Ohio State University. My research interests are broadly in the area of political communication, with special interests in social identity, social environments, and the maintenance thereof. I also spend a good deal of my time thinking about the research designs and analytic methods we can use to learn more about these things.
PhD in Communication (expected), 2020
Ohio State University
MA in Communication, 2019
Ohio State University
BA with Honors in Political Science, 2014
An expanding collection of tools I’ve created to aid in my own research. Most popular are functions that provide a streamlined, customizable summary of regressions (including robust standard error support) in the console, HTML/LaTeX/Word tables, and coefficient plots. A few other tools have been described in my blog and elsewhere.
Previously part of the
jtools package, this provides a set of functions that aid the analysis of statistical interactions. It implement simple slopes analysis, the calculation of Johnson-Neyman intervals, and plots for understanding interaction effects.
This is the Ruby-based command line tool I wrote to collect the music-related data that were content-analyzed in Long & Eveland (2019).
This is an R package that contains tools for the management and analysis of panel data. The main contributions are a
panel_data object class designed to make panel-specific functions easier to handle and
wbm, a procedure for fitting within-between regression models.
This R package implements a technique from Allison, Williams, and Moral-Benito (2017) and the Stata command
xtdpdml. It combines maximum likelihood estimation, the logic of cross-lagged panel models, and the robustness to spuriousness of fixed effects estimators into
dpm, dynamic panel models. Written with help from Richard Williams and Paul Allison.
A template for writing reports in APA format using the LaTeX typesetting engine. The heavy lifting is done by the
apa6 package, but this saves the user some time writing out code to get started.
This is a Shiny app to demonstrate to students how much randomly assigned groups can differ on some measure without it actually being a significant difference.
panelr, to the wider world. There’s at least one comparable package for R, called
plm, which is very good and should be particularly appealing for economists. This leads to the understandable question as to how
Zotero is a major part of my workflow from gathering research to the final, written output. One major annoyance, though, is its interpretation of APA reference style. It’s all correct, of course, with one exception: It adds the issue number to every journal citation.
survey package is one of R’s best tools for those working in the
social sciences. For many, it saves you from needing to use commercial
software for research that uses survey data. However, it lacks one
function that many academic researchers often need to report in
publications: correlations. The
svycor function in
(more info) helps to
fill that gap.