A practical guide to adopting transparent and reproducible practices in statistically orientated social science research during COVID-19

The unprecedented nature of the COVID-19 global pandemic has had momentously disruptive effects on contemporary social life. The empirical findings that flow from social science inquiries have important implications for establishing policies and changing practices. The speed at which the pandemic has unfolded has led to a previously unparalleled requirement for rapid results from social science studies. This acceleration has consequences for verifying empirical results, and for building incrementally on research findings.

This guide considers the methodological issues associated with undertaking transparent and reproducible social science research and provides a set of recommendations. The focus of this guide is social science research that employs statistical techniques for the analysis of large-scale and complex datasets (e.g. social surveys, administrative social science data and big data resources); however many of the issues pervade other forms of social science research.