The recognition that researcher discretion coupled with unconscious biases and motivated reasoning sometimes leads to false findings ("p-hacking") led to the broad embrace of study preregistration and other open-science practices in experimental research. Paradoxically, the preregistration of quasi-experimental studies remains uncommon although such studies involve far more discretionary decisions and are the most prevalent approach to making causal claims in the social sciences. I discuss several forms of recent empirical evidence indicating that questionable research practices contribute to the comparative unreliability of quasi-experimental research and advocate for adopting the preregistration of such studies. The implementation of this recommendation would benefit from further consideration of key design details (e.g., how to balance data cleaning with credible preregistration) and a shift in research norms to allow for appropriately nuanced sensemaking across prespecified, confirmatory results and other exploratory findings.
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http://dx.doi.org/10.1177/0193841X251326738 | DOI Listing |
Eval Rev
March 2025
Graduate School of Education, Stanford University, Stanford, CA, USA.
The recognition that researcher discretion coupled with unconscious biases and motivated reasoning sometimes leads to false findings ("p-hacking") led to the broad embrace of study preregistration and other open-science practices in experimental research. Paradoxically, the preregistration of quasi-experimental studies remains uncommon although such studies involve far more discretionary decisions and are the most prevalent approach to making causal claims in the social sciences. I discuss several forms of recent empirical evidence indicating that questionable research practices contribute to the comparative unreliability of quasi-experimental research and advocate for adopting the preregistration of such studies.
View Article and Find Full Text PDFJ Appl Behav Anal
October 2024
Department of Teaching and Learning, Temple University, Philadelphia, PA, USA.
Open science practices are designed to enhance the utility, integrity, and credibility of scientific research. This article highlights how preregistration in open science practice can be leveraged to enhance the rigor and transparency of single-case experimental designs within an applied behavior analysis framework. We provide an overview of the benefits of preregistration including increased transparency, reduced risk of researcher bias, and improved replicability, and we review the specific contexts under which these practices most benefit the proposed framework.
View Article and Find Full Text PDFSci Rep
September 2022
Milan Center for Neuroscience, University of Milano-Bicocca, 20126, Milan, Italy.
Artificial Intelligence (AI) systems are precious support for decision-making, with many applications also in the medical domain. The interaction between MDs and AI enjoys a renewed interest following the increased possibilities of deep learning devices. However, we still have limited evidence-based knowledge of the context, design, and psychological mechanisms that craft an optimal human-AI collaboration.
View Article and Find Full Text PDFEur J Neurosci
January 2021
Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
In neuroimaging studies, small sample sizes and the resultant reduced statistical power to detect effects that are not large, combined with inadequate analytic choices, concur to produce inflated or false-positive findings. To mitigate these issues, researchers often restrict analyses to specific brain areas, using the region of interest (ROI) approach. Crucially, ROI analysis assumes the a priori justified definition of the target region.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!