Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis

Jeffrey J. Starns, Andrea M. Cataldo, Caren M. Rotello, Jeffrey Annis, Andrew Aschenbrenner, Arndt Bröder, Gregory Cox, Amy Criss, Ryan A. Curl, Ian G. Dobbins, John Dunn, Tasnuva Enam, Nathan J. Evans, Simon Farrell, Scott H. Fraundorf, Scott D. Gronlund, Andrew Heathcote, Daniel W. Heck, Jason L. Hicks, Mark J. HuffDavid Kellen, Kylie N. Key, Asli Kilic, Karl Christoph Klauer, Kyle R. Kraemer, Fábio P. Leite, Marianne E. Lloyd, Simone Malejka, Alice Mason, Ryan M. McAdoo, Ian M. McDonough, Robert B. Michael, Laura Mickes, Eda Mizrak, Shane T. Mueller, Adam Osth, Angus Reynolds, Travis M. Seale-Carlisle, Henrik Singmann, Jennifer F. Sloane, Gabriel Tillman, Don van Ravenzwaaij, Christoph T. Weidemann, Gary L. Wells, Corey N. White, Jack Wilson

Research output: Contribution to journalArticle

Abstract

Scientific advances across a range of disciplines hinge on the ability to make inferences about unobservable theoretical entities on the basis of empirical data patterns. Accurate inferences rely on both discovering valid, replicable data patterns and accurately interpreting those patterns in terms of their implications for theoretical constructs. The replication crisis in science has led to widespread efforts to improve the reliability of research findings, but comparatively little attention has been devoted to the validity of inferences based on those findings. Using an example from cognitive psychology, we demonstrate a blinded-inference paradigm for assessing the quality of theoretical inferences from data. Our results reveal substantial variability in experts? judgments on the very same data, hinting at a possible inference crisis.
Original languageEnglish
Pages (from-to)335-349
Number of pages15
JournalAdvances in Methods and Practices in Psychological Science
Volume2
Issue number4
DOIs
Publication statusE-pub ahead of print - 17 Sep 2019

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