Combining multiple survey sources: A reproducible workflow and toolbox for survey data harmonization

Abstract

Ex-post harmonization of survey data creates new opportunities for research by extending the geographical and/or time coverage of analyses. Researchers increasingly combine data from different survey projects to analyze them as a single dataset, and while teams engaged in data harmonization continue to expand the information they provide to end users, there are still no commonly agreed standards for the documentation of data processing. Existing harmonization project typically opt for recode scripts that are generally hard to read, modify, and reuse, although some projects make efforts to facilitate verification and reproduction. This paper describes an alternative procedure and a set of simple tools for the exploration, recoding, and documentation of harmonization of survey data, relying on crosswalks. The presented tools are flexible and software-agnostic. The illustrative example uses the programming language R and spreadsheets—both common software choices among social scientists. Harmonization of variables on trust in institutions from four major cross-national survey projects serves as an illustration of the proposed workflow and of opportunities harmonization creates.