Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-26T15:09:31.178Z Has data issue: false hasContentIssue false
  • English
  • Français

We need to be braver about the generalizability crisis

Published online by Cambridge University Press:  10 February 2022

Todd S. Braver Open the ORCID record for Todd S. Braver [Opens in a new window]  and
Sanford L. Braver
Todd S. Braver
Affiliation:
Department of Psychological & Brain Sciences, Washington University, St. Louis, St. Louis, MO63130, USAtbraver@wustl.edu; http://ccpweb.wustl.edu
Sanford L. Braver
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ85287, USAsanford.braver@asu.edu; http://www.public.asu.edu/~devra1/
Get access Rights & Permissions [Opens in a new window]

Abstract

We applaud the effort to draw attention to generalizability concerns in twenty-first-century psychological research. Yet we do not feel that a pessimistic perspective is warranted. We outline a continuum of available methodological tools and perspectives, including incremental steps and meta-analytic approaches that can be readily and easily deployed by researchers to advance generalizability claims in a forward-looking manner.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e6
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baribault, B., Donkin, C., Little, D. R., Trueblood, J. S., Oravecz, Z., van Ravenzwaaij, D., … Vandekerckhove, J. (2018). Metastudies for robust tests of theory. Proceedings of the National Academy of Sciences, 115(11), 201708285. https://doi.org/10.1073/pnas.1708285114.CrossRefGoogle ScholarPubMed
Braver, S. L., Thoemmes, F. J., & Rosenthal, R. (2014). Continuously cumulating meta-analysis and replicability. Perspectives on Psychological Science, 9(3), 333–342. https://doi.org/10.1177/1745691614529796.CrossRefGoogle ScholarPubMed
Brunswik, E. (1956). Perception and the representative design of psychological experiments (2nd ed.). University of California Press.CrossRefGoogle Scholar
Campbell, D. T., & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Rand-McNally.Google Scholar
Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Rand-McNally.Google Scholar
Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American Psychologist, 30(2), 116–127. https://doi.org/https://psycnet-apa-org.libproxy.wustl.edu/doi/10.1037/h0076829.CrossRefGoogle Scholar
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Academic Press. https://doi.org/https://doi.org/10.1016/C2009-0-03396-0.Google Scholar
Scheibehenne, B., Jamil, T., & Wagenmakers, E.-J. (2016). Bayesian evidence synthesis can reconcile seemingly inconsistent results. Psychological Science, 27(7), 1043–1046. https://doi.org/10.1177/0956797616644081.CrossRefGoogle ScholarPubMed
Schooler, J. W., & Engstler-Schooler, T. Y. (1990). Verbal overshadowing of visual memories: Some things are better left unsaid. Cognitive Psychology, 22(1), 36–71. https://doi.org/10.1016/0010-0285(90)90003-m.CrossRefGoogle ScholarPubMed
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin and Company.Google Scholar