Denis Cohen, Cosima Meyer, Marcel Neunhoeffer, Oliver Rittmann
Efficient Data Management in R

MZES Methods Bites - Blog of the MZES Social Science Data Lab. 2020. Mannheim: MZES

The software environment R is widely used for data analysis and data visualization in the social sciences and beyond. Additionally, it is becoming increasingly popular as a tool for data and file management. Focusing on these latter aspects, this Methods Bites Tutorial by Marcel Neunhoeffer, Oliver Rittmann and our team members Denis Cohen and Cosima Meyer illustrates the workflow and best practices for efficient data management in R. Readers will learn about: the workflow for organizing and conducting complex analyses in R creating, editing, and accessing directory hierarchies and their contents data merging, data management and data manipulation using tidy R and base R the basics of programming and debugging To illustrate these steps, we will work through an example from comparative political behavior – the question under which conditions center-left parties can successfully mobilize votes among the unemployed. To tackle this question, we will combine micro-level voting data from Round 9 of the European Social Survey with contextual data on election dates from ParlGov, party positions from the Manifesto Project, and unemployment rates from the World Bank. Note: This blog post is based on our workshop in the MZES Social Science Data Lab in Spring 2020. The corresponding workshop materials can be found on our GitHub.