R-Ladies Dallas Jan 25, 2021: Reproducible workflows with Dr. Seo-young Silvia Kim

Abstract: College and Ph.D. students who do empirical work often underestimate the problems associated with reproducibility. Certain lessons should be shared for those entering the research phase, which will help not to struggle or waste time later. From setting up an R project to using renv, I discuss some of the most important things that new researchers should be mindful of when starting a new data analysis project.
Bio: I am an Assistant Professor in the Department of Government at American University. I received my Ph.D. from the California Institute of Technology in 2020. My research interests are in American Politics and Political Methodology, focusing on political behavior (registration/turnout/campaign contributions), working with large voter files and Federal Election Commission datasets. I mainly use R and Stan to employ tools such as probabilistic record linkage, semiparametric regressions, machine learning, and Bayesian statistics.