Note: PLOS is delighted to once again partner with the Einstein Foundation Award for Promoting Quality in Research. The awards program honors…
Improving analytical standards: Global Analytical Robustness Initiative
Note: PLOS is delighted to once again partner with the Einstein Foundation Award for Promoting Quality in Research. The awards program honors researchers who reflect rigor, reliability, robustness, and transparency in their work. The Einstein Foundation received dozens of stellar submissions. We asked this year’s finalists to write about their research in the run up to the ceremony on March 14th in Berlin. This is the last blog in our 5-part series.
Every research study involves numerous potential outcomes and conclusions, as researchers employ diverse analytical approaches when interpreting empirical data. Recognizing the variability in these methods, my colleagues from the University of Innsbruck, Stanford University, and Dartmouth College, along with myself, have established the Global Analytical Robustness Initiative.
The primary goal of this initiative is to enhance analytical standards within the behavioral and social sciences, thereby boosting the reliability and transparency of research outcomes. The team’s plan is to have 100 studies examined by around 500 experts for analytical robustness and create an open database that makes transparent the correlation between the analytical paths taken in empirical work and the results presented in the research.
The project will enable researchers to identify and respond to the corresponding problems and challenges. On this basis, the Global Analytical Robustness Initiative aims to issue recommendations on how to increase analytical robustness and train scientists to use the most robust analytical methodologies. “In this way, we hope to strengthen the reliability of future empirical results and, ultimately, foster trust in science.”
Author: Barnabás Szászi leads the work of the Behavioral Science lab and the Behavioral Science Center for Good. His primary goal is to support vulnerable individuals and groups (families, the poor and the sad) using behavioral and data science. He obtained a dual degree in psychology and economics and finished my Ph.D. in experimental psychology in 2018. Since then, his work as a lead author appeared in top psychology and social science journals such as Proceedings of the National Academy of Sciences, Nature Human Behaviour, Journal of Behavioral Decision Making, and eLife. He has won numerous scholarships and awards including the scholarship of the Hungarian Central Bank, the National Excellence Program, Bolyai, Campus Mundi, Eötvös, Rosztóczy, Fulbright (2x), and the Promising Researcher and the Rosak Tamas award. He was also a visiting student researcher at Columbia University and is now an incoming Fulbright Scholar at Harvard Business School for the academic year 2023/24.