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.

Mental health data available in representative surveys conducted in Latin America and the Caribbean countries: a scoping review

“…When using more than one database at a time, consider differences in sampling procedures and weights, or that some variables are not directly comparable/fissionable (eg, raw scales from different depression tests). In general, a formal data harmonisation process is required 33 34. Data harmonisation processes between different surveys, or between historical data from the same survey, would inform public and global mental health decision-making.…”

“…In general, a formal data harmonisation process is required. 33 34 Data harmonisation processes between different surveys, or between historical data from the same survey, would inform public and global mental health decision-making. We suggest reviewing the tutorial by Zhao et al as an example of data harmonisation with complex sampling.…”

Accelerating Social Science Knowledge Production with the Coordinated Open-Source Model

“…Instead, CNEF's developers are responsible for providing credible and ultimate harmonisation solutions. However, multiple standards and strategies for ex-post harmonisation methodology exist (Dubrow & Tomescu-Dubrow 2016;Kołczyńska 2022). Household panel survey harmonization initiatives were also criticized for being dominated by a single field, i.e., economics, and focused on factors and variables relevant to economic research, such as income and wealth (Dubrow & Tomescu-Dubrow 2016).…”

Visualizing Data Interoperability for Food Systems Sustainability Research—From Spider Webs to Neural Networks

“…A crosswalk denotes the connection of 2 data sources through a common set of identifiers or indices, which can be used to link, merge, or join the data [ 23 , 24 ]. To better understand the nature of crosswalks, we assessed each data source for a documented relationship with other data sources in our demonstration sample.…”