Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis. Issue 4 (December 2019)

• Record Type: Journal Article
• Authors: Starns, Jeffrey J.; Cataldo, Andrea M.; Rotello, Caren M.; Annis, Jeffrey; Aschenbrenner, Andrew; Bröder, Arndt; Cox, Gregory; Criss, Amy; Curl, Ryan A.; Dobbins, Ian G.; Dunn, John; Enam, Tasnuva; Evans, Nathan J.; Farrell, Simon; Fraundorf, Scott H.; Gronlund, Scott D.; Heathcote, Andrew; Heck, Daniel W.; Hicks, Jason L.; Huff, Mark J.; Kellen, David; Key, Kylie N.; Kilic, Asli; Klauer, Karl Christoph; Kraemer, Kyle R.; Leite, Fábio P.; Lloyd, Marianne E.; Malejka, Simone; Mason, Alice; McAdoo, Ryan M.; McDonough, Ian M.; Michael, Robert B.; Mickes, Laura; Mizrak, Eda; Morgan, David P.; Mueller, Shane T.; Osth, Adam; Reynolds, Angus; Seale-Carlisle, Travis M.; Singmann, Henrik; Sloane, Jennifer F.; Smith, Andrew M.; Tillman, Gabriel; van Ravenzwaaij, Don; Weidemann, Christoph T.; Wells, Gary L.; White, Corey N.; Wilson, Jack;
• Is Part Of: Advances in methods and practices in psychological science. Volume 2:Issue 4(2019)
• Page Start: 335
• Page End: 349
• Publication Date: 2019-12
• Subjects: memory -- modeling -- Bayesian methods -- bootstrap -- metascience -- blinded inference -- open data; Psychology -- Periodicals; Psychology -- Research -- Periodicals; 150
• DOI: 10.1177/2515245919869583
• Languages: English
• ISSNs: 2515-2459

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 .