Protecting against researcher bias in secondary data analysis: Challenges and potential solutions

Jessie Baldwin; Jean-Baptiste Pingault; Tabea Schoeler; Hannah M Sallis; Marcus R Munafo

doi:10.1007/s10654-021-00839-0

Protecting against researcher bias in secondary data analysis: Challenges and potential solutions

Jessie Baldwin^*, Jean-Baptiste Pingault, Tabea Schoeler, Hannah M Sallis, Marcus R Munafo

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society’s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data.

Original language	English
Pages (from-to)	1–10
Journal	European Journal of Epidemiology
Volume	37
Issue number	1
Early online date	13 Jan 2022
DOIs	https://doi.org/10.1007/s10654-021-00839-0
Publication status	E-pub ahead of print - 13 Jan 2022

Bibliographical note

Funding Information:
J.R.B is funded by a Wellcome Trust Sir Henry Wellcome fellowship (grant 215917/Z/19/Z). J.B.P is a supported by the Medical Research Foundation 2018 Emerging Leaders 1 Prize in Adolescent Mental Health (MRF-160–0002-ELP-PINGA). M.R.M and H.M.S work in a unit that receives funding from the University of Bristol and the UK Medical Research Council (MC_UU_00011/5, MC_UU_00011/7), and M.R.M is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. st

Publisher Copyright:
© 2022, The Author(s).

Keywords

Secondary data analysis
Pre-registration
Open science
Researcher bias

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title = "Protecting against researcher bias in secondary data analysis: Challenges and potential solutions",

abstract = "Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society{\textquoteright}s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data. ",

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author = "Jessie Baldwin and Jean-Baptiste Pingault and Tabea Schoeler and Sallis, \{Hannah M\} and Munafo, \{Marcus R\}",

note = "Funding Information: J.R.B is funded by a Wellcome Trust Sir Henry Wellcome fellowship (grant 215917/Z/19/Z). J.B.P is a supported by the Medical Research Foundation 2018 Emerging Leaders 1 Prize in Adolescent Mental Health (MRF-160–0002-ELP-PINGA). M.R.M and H.M.S work in a unit that receives funding from the University of Bristol and the UK Medical Research Council (MC\_UU\_00011/5, MC\_UU\_00011/7), and M.R.M is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. st Publisher Copyright: {\textcopyright} 2022, The Author(s).",

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N2 - Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society’s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data.

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Protecting against researcher bias in secondary data analysis: Challenges and potential solutions

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