Large-Scale Replication Projects in Contemporary Psychological Research
Blakeley B. McShane,
Jennifer L. Tackett,
Ulf Böckenholt and
Andrew Gelman
The American Statistician, 2019, vol. 73, issue S1, 99-105
Abstract:
Replication is complicated in psychological research because studies of a given psychological phenomenon can never be direct or exact replications of one another, and thus effect sizes vary from one study of the phenomenon to the next—an issue of clear importance for replication. Current large-scale replication projects represent an important step forward for assessing replicability, but provide only limited information because they have thus far been designed in a manner such that heterogeneity either cannot be assessed or is intended to be eliminated. Consequently, the nontrivial degree of heterogeneity found in these projects represents a lower bound on the true degree of heterogeneity. We recommend enriching large-scale replication projects going forward by embracing heterogeneity. We argue this is the key for assessing replicability: if effect sizes are sufficiently heterogeneous—even if the sign of the effect is consistent—the phenomenon in question does not seem particularly replicable and the theory underlying it seems poorly constructed and in need of enrichment. Uncovering why and revising theory in light of it will lead to improved theory that explains heterogeneity and increases replicability. Given this, large-scale replication projects can play an important role not only in assessing replicability but also in advancing theory.
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2018.1505655 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:amstat:v:73:y:2019:i:s1:p:99-105
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20
DOI: 10.1080/00031305.2018.1505655
Access Statistics for this article
The American Statistician is currently edited by Eric Sampson
More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().