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14 pt periods. 1.05” margins. 2.1 spaced lines. Times Newer Roman. I’ve seen them all, and I’m tired of trying to catch them. So, I’ve stopped assigning papers in terms of page length and switched to word counts. Unfortunately, counting words is more time-intensive than counting pages.
Everyone knows that Beamer makes frankly terrible presentations without a good deal of help. A well crafted Beamer presentation can be a thing of beauty, especially since you can use knitr or R Markdown to automatically generate tables and figures, but it takes a lot of work.
I’m currently cleaning and wrangling a large (> 2 billion observations) dataset. Due to its size, I’m running code in batch mode on a remote cluster. Not running interactively makes it harder for me to check on my code’s progress.
I recently updated my CV to add my ORCiD identifier to it up top among the other places to find me online. An ORCiD is an online identifier that persists through any changes to your name, institution, or email address throughout your life.
My previous post on combining multiple PDF files had an important caveat that things would end up in the wrong order if you had files with leading ID numbers that started at 1 and ended at 12, you’d end up with PDFs combined in the order 1, 10, 11, 12, 2, 3, …, 9.
How many times have you found that your institution has access to a digital version of a book you need only to discover that it comes in 15 different PDF files?
Published in Political Science Research and Methods, 2019
Recommended citation: Williams, Rob, Daniel J. Gustafson, Stephen E. Gent, and Mark J.C. Crescenzi. (Forthcoming). "A Latent Variable Approach to Measuring and Explaining Peace Agreement Strength." Political Science Research and Methods. doi:10.1017/psrm.2019.23
BayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimation Permalink
Published in Journal of Open Source Software, 2019
Recommended citation: Scogin, Shana, Johannes Karreth, Andreas Beger, and Rob Williams. (2019). "BayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimation." Journal of Open Source Software. 4(42), 1722, doi:10.21105/joss.01722
Using images to uncover hidden relationships
How states identify and thwart nascent separatist movements
Exploring the microlevel dynamics of conflict
Measuring and explaining elusive concepts
Models for spatially correlated data