This section contains a list of external resources providing guidance on conducting data harmonisation below.
You can also explore the resources on measurement invariance and standardised scales using the navigation links on this page.
This paper, published in Discovery Social Science and Health, discusses the key challenges researchers face when carrying out comparative research. It also provides a structured checklist to guide researchers carrying out or reviewing cross-study research.
CODE: The paper also provides open-access teaching resources demonstrating the key steps for cross-study research. These are provided in R and Stata languages.
This paper, published in the International Journal of Epidemiology, outlines some guidelines for retrospective data harmonisation to ensure quality, reproducibility, and transparency of the data harmonisation process.
Blog series: Harmonisation adventures
This blog series discusses retrospective (ex-post) data harmonisation and shares some insights from the GESIS team. Topics include:
- How to determine if two questions measure the same concept
- Different statistical approaches to make variables comparable
- Multiple imputation to harmonise data
- Control variables to help determine quality and comparability of source data
Online resource: GSS harmonisation support
This resource outlines the harmonisation initiatives by government statisticians and data scientists, including harmonisation standards and guidance for different topics and examples of successful harmonisation within government.
Online resource: Guidance hub
The Government Analysis Function hosts a Guidance hub with resources and reference information for data analysis. Search for “Harmonisation standards and guidance” to see tools for improving the comparability and coherence of statistics, including standards for socioeconomic background, mental health, disability, and ethnicity.
Online resource: Measurement Toolkit – harmonisation
This toolkit covers what harmonisation is, when it is needed, and how it is conducted.
Working Paper series: Gateway to Global Aging Data: Cross-country comparability
A working paper series on cross-country comparability of their ageing studies across multiple themes, as well as information on concordance across the surveys.
Guidelines: Cross-Cultural Survey Guidelines
Guidelines highlighting best practice for conducting multinational, multicultural, or multiregional surveys. They are split into chapters which cover all aspects of the survey lifecycle and include a section on Data harmonisation from the perspective of survey methodology.