Equality, equity, diversity, and inclusion principles: how should we apply these to statistical methodology research?

Abstract

Background

The aim of equality, equity, diversity, and inclusion (EDI) is to ensure fair treatment, equal opportunities, equitable outcomes, and representation. The NIHR Research Design Service (RDS) EDI toolkit (https://www.rssleicesterresources.org.uk/edi-toolkit) helps researchers embed EDI throughout their work. This study evaluated the applicability of the RDS EDI toolkit for statistical methodology research and proposed adaptations to enable statistical methodologists to embed EDI in their research.

Methods

A full-day meeting was held to consider how the RDS EDI toolkit could inform the inclusion of EDI principles in statistical methodology research. Twelve individuals attended from the University of Leicester and the NIHR Research Support Service (RSS) Hub delivered by the University of Leicester and Partners. At the meeting, definitions of statistical methodology research and EDI were agreed. The RDS EDI Toolkit was interrogated to identify relevant aspects and additional considerations for statistical methodology research.

Results

Overall, the RDS EDI toolkit was valuable for incorporating EDI in statistical methodology research. Five recommendations to supplement the toolkit are proposed to reflect specific EDI challenges for statistical methodology research. Statistical methodology researchers should:

1. 1.

Perform formal assessments of the required resources for maximising EDI from the outset of statistical methodology research projects, including consideration of research team, training, patient and public involvement, and appropriate budgeting.

2. 2.

Conduct prospective and retrospective context-specific evaluations of the impact of their methodological research on exacerbating or reducing inequalities.

3. 3.

Evaluate the selection of data sets, work with multiple, diverse databases, or use data sets that have undergone equality impact assessments.

4. 4.

Clearly communicate EDI assessments and limitations, including which data sets are used and their purpose, such as illustrating or comparing methods, informing simulations, or guiding clinical practice.

5. 5.

Incorporate EDI in dissemination activities and advocate for EDI principles in the peer review process.

Conclusions

Embedding EDI principles throughout statistical methodology research will improve its relevance and quality, better serve the public, and build public trust. It is essential that statistical methodologists strive towards equity in all aspects of their work. This paper demonstrates the value of the NIHR RDS EDI toolkit for statistical methodology research and encourages methodologists to adopt the recommendations in this paper. Further extensions to this work are needed to seek the wider views and experiences of statistical methodologists and public contributors from diverse and under-represented groups.