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Billet publié sur Bluesky le 13/10/2023 21:28

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Robert T. Thibault, Marton Kovacs, Tom E. Hardwicke, Alexandra Sarafoglou, John P. A. Ioannidis, Marcus R. Munafò (2023). Reducing bias in secondary data analysis via an Explore and Confirm Analysis Workflow (ECAW): a proposal and survey of observational researchers. Royal Society Open Science, 10(10), 230568. The Royal Society.

Date de publication
11/10/2023
Identifiant
10.1098/rsos.230568
Auteurs
Robert T. Thibault, Marton Kovacs, Tom E. Hardwicke, Alexandra Sarafoglou, John P. A. Ioannidis, Marcus R. Munafò
Source
Royal Society Open Science
Détails
10(10), 230568
Type de référence
article
Éditeur
The Royal Society
Source de métadonnées
crossref

Résumé

Background. Although preregistration can reduce researcher bias and increase transparency in primary research settings, it is less applicable to secondary data analysis. An alternative method that affords additional protection from researcher bias, which cannot be gained from conventional forms of preregistration alone, is an Explore and Confirm Analysis Workflow (ECAW). In this workflow, a data management organization initially provides access to only a subset of their dataset to researchers who request it. The researchers then prepare an analysis script based on the subset of data, upload the analysis script to a registry, and then receive access to the full dataset. ECAWs aim to achieve similar goals to preregistration, but make access to the full dataset contingent on compliance. The present survey aimed to garner information from the research community where ECAWs could be applied—employing the Avon Longitudinal Study of Parents and Children (ALSPAC) as a case example. Methods. We emailed a Web-based survey to researchers who had previously applied for access to ALSPAC's transgenerational observational dataset. Results. We received 103 responses, for a 9% response rate. The results suggest that—at least among our sample of respondents—ECAWs hold the potential to serve their intended purpose and appear relatively acceptable. For example, only 10% of respondents disagreed that ALSPAC should run a study on ECAWs (versus 55% who agreed). However, as many as 26% of respondents agreed that they would be less willing to use ALSPAC data if they were required to use an ECAW (versus 45% who disagreed). Conclusion. Our data and findings provide information for organizations and individuals interested in implementing ECAWs and related interventions. Preregistration. https://osf.io/g2fw5 Deviations from the preregistration are outlined in electronic supplementary material A.

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