The meaningfulness of effect sizes in psychological research: differences between sub-disciplines and the impact of potential biases
Open accessAbstract
Effect sizes are the currency of psychological research. They quantify the results of a study to answer the research question and are used to calculate statistical power. The interpretation of effect sizes—when is an effect small, medium, or large?—has been guided by the recommendations Jacob Cohen gave in his pioneering writings starting in 1962: Either compare an effect with the effects found in past research or use certain conventional benchmarks. The present analysis shows that neither of these recommendations is currently applicable. From past publications without pre-registration, 900 effects were randomly drawn and compared with 93 effects from publications with pre-registration, revealing a large difference: Effects from the former (median r = .36) were much larger than effects from the latter (median r = .16). That is, certain biases, such as publication bias or questionable research practices, have caused a dramatic inflation in published effects, making it difficult to compare an actual effect with the real population effects (as these are unknown). In addition, there were very large differences in the mean effects between psychological sub-disciplines and between different study designs, making it impossible to apply any global benchmarks. Many more pre-registered studies are needed in the future to derive a reliable picture of real population effects.
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,588 · see citing works
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099 · see citing works
Why Most Published Research Findings Are False
Ioannidis, J. P. A. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020124 · Cited by 10,505 · see citing works
Lakens, D. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00863 · Cited by 10,303 · see citing works
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771 · see citing works
Estimating the reproducibility of psychological science
Open Science Collaboration (2015) · Science · doi:10.1126/science.aac4716 · Cited by 8,515 · see citing works
Effect size estimates: Current use, calculations, and interpretation.
Fritz, C. O., Morris, P. E., & Richler, J. J. (2012) · Journal of Experimental Psychology: General · doi:10.1037/a0024338 · Cited by 5,199 · see citing works
The New Statistics: Why and How
Cumming, G. (2014) · Psychological Science · doi:10.1177/0956797613504966 · Cited by 3,200 · see citing works
Effect size guidelines for individual differences researchers
Gignac, G. E., & Szodorai, E. T. (2016) · Personality and Individual Differences · doi:10.1016/j.paid.2016.06.069 · Cited by 2,860 · see citing works
Ellis, P. D. (2010) · doi:10.1017/cbo9780511761676 · Cited by 2,461 · see citing works
Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling
John, L. K., Loewenstein, G., & Prelec, D. (2012) · Psychological Science · doi:10.1177/0956797611430953 · Cited by 2,239 · see citing works
Book Review: Design and Analysis: A Researcher's Handbook
Aaker, D. A., & Keppel, G. (1976) · Journal of Marketing Research · doi:10.2307/3150757 · Cited by 2,033 · see citing works
The statistical power of abnormal-social psychological research: A review.
Cohen, J. (1962) · The Journal of Abnormal and Social Psychology · doi:10.1037/h0045186 · Cited by 1,824 · see citing works
Things I have learned (so far).
Cohen, J. (1990) · American Psychologist · doi:10.1037/0003-066x.45.12.1304 · Cited by 1,781 · see citing works
Practical significance: a concept whose time has come
Kirk, R. E. (1996) · Educational and Psychological Measurement · doi:10.1177/0013164496056005002 · Cited by 1,778 · see citing works
Olejnik, S., & Algina, J. (2003) · Psychological Methods · doi:10.1037/1082-989x.8.4.434 · Cited by 1,622 · see citing works
One Hundred Years of Social Psychology Quantitatively Described
Richard, F. D., Bond, C. F., & Stokes-Zoota, J. J. (2003) · Review of General Psychology · doi:10.1037/1089-2680.7.4.331 · Cited by 1,558 · see citing works
Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M. (2018) · American Psychologist · doi:10.1037/amp0000191 · Cited by 1,449 · see citing works
Statistical Power Analysis for the Behavioral Sciences
Wassertheil, S., & Cohen, J. (1970) · Biometrics · doi:10.2307/2529115 · Cited by 1,383 · see citing works
Negative results are disappearing from most disciplines and countries
Fanelli, D. (2012) · Scientometrics · doi:10.1007/s11192-011-0494-7 · Cited by 1,248 · see citing works
Interpreting the magnitudes of correlation coefficients.
Hemphill, J. F. (2003) · American Psychologist · doi:10.1037/0003-066x.58.1.78 · Cited by 1,237 · see citing works
An Agenda for Purely Confirmatory Research
Wagenmakers, E.-J., Wetzels, R., Borsboom, D., van der Maas, H. L. J., & Kievit, R. A. (2012) · Perspectives on Psychological Science · doi:10.1177/1745691612463078 · Cited by 1,042 · see citing works
Kelley, K., & Preacher, K. J. (2012) · Psychological Methods · doi:10.1037/a0028086 · Cited by 1,002 · see citing works
The rules of the game called psychological science
Bakker, M., van Dijk, A., & Wicherts, J. M. (2012) · Perspectives on Psychological Science · doi:10.1177/1745691612459060 · Cited by 800 · see citing works
Do studies of statistical power have an effect on the power of studies?
Sedlmeier, P., & Gigerenzer, G. (1989) · Psychological Bulletin · doi:10.1037/0033-2909.105.2.309 · Cited by 748 · see citing works
<i>p</i> -Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results
Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014) · Perspectives on Psychological Science · doi:10.1177/1745691614553988 · Cited by 717 · see citing works
The Replication Recipe: What makes for a convincing replication?
Brandt, M. J., IJzerman, H., Dijksterhuis, A., Farach, F. J., Geller, J., Giner‐Sorolla, R., Grange, J. A., Perugini, M., Spies, J. R., & Veer, A. V. '. (2013) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2013.10.005 · Cited by 703 · see citing works
Standardized or simple effect size: what should be reported?
Baguley, T. (2009) · British Journal of Psychology · doi:10.1348/000712608x377117 · Cited by 619 · see citing works
An Open, Large-Scale, Collaborative Effort to Estimate the Reproducibility of Psychological Science
Open Science Collaboration (2012) · Perspectives on Psychological Science · doi:10.1177/1745691612462588 · Cited by 605 · see citing works
Fraley, R. C., & Vazire, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0109019 · Cited by 409 · see citing works
Reporting effect sizes in original psychological research: A discussion and tutorial.
Pek, J. C. X., & Flora, D. B. (2017) · Psychological Methods · doi:10.1037/met0000126 · Cited by 321 · see citing works
Meta-analysis using effect size distributions of only statistically significant studies.
van Assen, M. A. L. M., van Aert, R. C. M., & Wicherts, J. M. (2015) · Psychological Methods · doi:10.1037/met0000025 · Cited by 265 · see citing works
(2016) · Cited by 252 · see citing works
Effect magnitude: A different focus
Kirk, R. (2007) · Journal of Statistical Planning and Inference · doi:10.1016/j.jspi.2006.09.011 · Cited by 101 · see citing works
A methodological review of meta-analyses of the effectiveness of clinical psychology treatments
Rubio‐Aparicio, M., Marín‐Martínez, F., Sánchez‐Meca, J., & López-López, J. A. (2017) · Behavior Research Methods · doi:10.3758/s13428-017-0973-8 · Cited by 93 · see citing works
Many Labs 2: Investigating Variation in Replicability Across Sample and SettingPreprint
Klein, R. A., Vianello, M., Hasselman, F., Adams, B. G., Adams, R. B., Alper, S., Aveyard, M. E., Axt, J., Babalola, M. T., Bahník, Š., et al. (2018) · doi:10.31234/osf.io/9654g · Cited by 81 · see citing works
Haase, R. F., Waechter, D. M., & Solomon, G. S. (1982) · Journal of Counseling Psychology · doi:10.1037/0022-0167.29.1.58 · Cited by 79 · see citing works
Effect sizes in memory research
Morris, P. E., & Fritz, C. O. (2013) · Memory · doi:10.1080/09658211.2013.763984 · Cited by 78 · see citing works
Cooper, H., & Findley, M. J. (1982) · Personality and Social Psychology Bulletin · doi:10.1177/014616728281026 · Cited by 53 · see citing works
The Power of Replications and Replications of Power
Ottenbacher, K. J. (1996) · The American Statistician · doi:10.1080/00031305.1996.10474398 · Cited by 32 · see citing works
Renkewitz, F., & Keiner, M. (2018) · doi:10.31234/osf.io/w94ep · Cited by 14 · see citing works
Die New Statistics in der Psychologie
Schäfer, T. (2018) · Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie · doi:10.1026/0049-8637/a000184 · Cited by 8 · see citing works
Flagged first, then by citations
1 of the 43 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Cohen J. (1977). Statistical Power Analysis for the Behavioral Sciences (revised Edn.). New York, NY: Academic Press.
- Keppel G. (1991). Design and Analysis: A Researcher’s Handbook. Englewood Cliffs, NJ: Prentice Hall.
Cited by
Sorted by citations
Interpreting effect sizes of education interventions
Kraft, M. A. (2020) · Educational Researcher · doi:10.3102/0013189x20912798 · Cited by 1,281 · see citing works
Effect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology
Brydges, C. R. (2019) · Innovation in Aging · doi:10.1093/geroni/igz036 · Cited by 826 · see citing works
Elliott, M. L., Knodt, A. R., Ireland, D., Morris, M. L., Poulton, R., Ramrakha, S., Sison, M. L., Moffitt, T. E., Caspi, A., & Hariri, A. R. (2020) · Psychological Science · doi:10.1177/0956797620916786 · Cited by 714 · see citing works
Empirically derived guidelines for effect size interpretation in social psychology
Lovakov, A. V., & Рафиковна, А. Е. (2021) · European Journal of Social Psychology · doi:10.1002/ejsp.2752 · Cited by 692 · see citing works
Small Effects: The Indispensable Foundation for a Cumulative Psychological Science
Götz, F. M., Gosling, S. D., & Rentfrow, P. J. (2021) · Perspectives on Psychological Science · doi:10.1177/1745691620984483 · Cited by 553 · see citing works
Evaluation of a decided sample size in machine learning applications
Rajput, D., Wang, W.-J., & Chen, C.-C. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05156-9 · Cited by 411 · see citing works
A Meta-Analytic Review of Preschool Social and Emotional Learning Interventions
Murano, D. M., Sawyer, J., & Lipnevich, A. A. (2020) · Review of Educational Research · doi:10.3102/0034654320914743 · Cited by 297 · see citing works
Meaningful associations in the adolescent brain cognitive development study
Dick, A. S., Lopez, D. A., Watts, A. L., Heeringa, S. G., Reuter, C., Bartsch, H., Fan, C. C., Kennedy, D. N., Palmer, C. E., Marshall, A. T., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118262 · Cited by 234 · see citing works
Sommet, N., Weissman, D. L., Cheutin, N., & Elliot, A. J. (2023) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459231178728 · Cited by 274 · see citing works
Power to Detect What? Considerations for Planning and Evaluating Sample Size
Giner‐Sorolla, R., Montoya, A. K., Reifman, A. S., Carpenter, T., Lewis, N. A., Aberson, C. L., Bostyn, D. H., Conrique, B. G., Ng, B., Schoemann, A. M., et al. (2024) · Personality and Social Psychology Review · doi:10.1177/10888683241228328 · Cited by 292 · see citing works
An Agenda for Open Science in Communication
Dienlin, T., Johannes, N., Bowman, N. D., Masur, P. K., Engesser, S., Kümpel, A. S., Lukito, J., Bier, L. M., Zhang, R., Johnson, B. K., et al. (2020) · Journal of Communication · doi:10.1093/joc/jqz052 · Cited by 221 · see citing works
Nudging: Progress to date and future directions
Beshears, J. L., & Kosowsky, H. (2020) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2020.09.001 · Cited by 197 · see citing works
Comparing meta-analyses and preregistered multiple-laboratory replication projects
Kvarven, A., Strømland, E., & Johannesson, M. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0787-z · Cited by 271 · see citing works
Editorial Perspective: When is a ‘small effect’ actually large and impactful?
Carey, E., Ridler, I., Ford, T. J., & Stringaris, A. K. (2023) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13817 · Cited by 198 · see citing works
Protecting against researcher bias in secondary data analysis: challenges and potential solutions
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Effect sizes for nonparametric tests
Peres, F. F. (2025) · Biochemia Medica · doi:10.11613/bm.2026.010101 · Cited by 241 · see citing works
Ejelöv, E., & Luke, T. J. (2019) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2019.103937 · Cited by 175 · see citing works
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Correll, J., Mellinger, C., McClelland, G. H., & Judd, C. M. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.12.009 · Cited by 167 · see citing works
Kohl, S. H., Mehler, D. M. A., Lührs, M., Thibault, R. T., Konrad, K., & Sorger, B. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00594 · Cited by 160 · see citing works
Burger, A., D’Agostini, M., Verkuil, B., & Diest, I. V. (2020) · Psychophysiology · doi:10.1111/psyp.13571 · Cited by 136 · see citing works
Owens, M. M., Potter, A., Hyatt, C. S., Albaugh, M. D., Thompson, W. K., Jernigan, T. L., Yuan, D., Hahn, S., Allgaier, N. A., & Garavan, H. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257535 · Cited by 157 · see citing works
How Firm Are the Foundations of Mind-Set Theory? The Claims Appear Stronger Than the Evidence
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#EEGManyLabs: Investigating the replicability of influential EEG experiments
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Gustafson, A., Ballew, M. T., Goldberg, M. H., Cutler, M., Rosenthal, S. A., & Leiserowitz, A. (2020) · Communication Reports · doi:10.1080/08934215.2020.1799049 · Cited by 124 · see citing works
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Visual Reasoning Strategies for Effect Size Judgments and Decisions
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Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan
Kupis, L. B., Goodman, Z. T., Kornfeld, S., Hoang, S., Romero, C., Dirks, B., Dehoney, J., Chang, C. E., Spreng, R. N., Nomi, J. S., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab156 · Cited by 103 · see citing works
Open and reproducible neuroimaging: From study inception to publication
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Mesquida, C., Murphy, J., Lakens, D., & Warne, J. P. (2022) · Royal Society Open Science · doi:10.1098/rsos.220946 · Cited by 98 · see citing works
Leichtmann, B., & Nitsch, V. (2020) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2019.101386 · Cited by 89 · see citing works
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“This suggests a need to look beyond the existing categorisation of effect sizes and locate other suitable indicators that may subsequently inform practice and policy (Kraft, 2020; Schäfer & Schwarz, 2019).”
BackgroundWischnewski, M., Mantell, K. E., & Opitz, A. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.08.017 · Cited by 79 · see citing works
Enhancing precision in human neuroscience
Nebe, S., Reutter, M., Baker, D. H., Bölte, J., Domes, G., Gamer, M., Gärtner, A., Gießing, C., Gurr, C., Hilger, K., et al. (2023) · eLife · doi:10.7554/elife.85980 · Cited by 75 · see citing works
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Ozimek, P., Lainas, S., Bierhoff, H., & Rohmann, E. (2023) · BMC Psychology · doi:10.1186/s40359-023-01143-0 · Cited by 95 · see citing works
Wild, H. A., Kyröläinen, A.-J., & Kuperman, V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271191 · Cited by 72 · see citing works
Effects of the Jigsaw method on student educational outcomes: systematic review and meta-analyses
Drouet, O., Lentillon‐Kaestner, V., & Margas, N. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1216437 · Cited by 123 · see citing works
Elliott, M. L., Knodt, A. R., Ireland, D. R., Morris, M. L., Poulton, R., Ramrakha, S., Sison, M. L., Moffitt, T. E., Caspi, A., & Hariri, A. R. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/681700 · Cited by 68 · see citing works
Tagliabue, M., Sigurjonsdottir, S. S., & Sandaker, I. (2020) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2020.1796647 · Cited by 90 · see citing works
Leichtmann, B., Nitsch, V., & Mara, M. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.838116 · Cited by 66 · see citing works
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Quintana, D. S. (2023) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459221147260 · Cited by 95 · see citing works
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The benefits of preregistration and Registered Reports
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Primbs, M. A., Pennington, C. R., Lakens, D., Silan, M. A. A., Lieck, D., Forscher, P. S., Buchanan, E. M., & Westwood, S. J. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221100420 · Cited by 62 · see citing works
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Mosquera, F. E. C., Martinez, S. L., & Liscano, Y. (2024) · Nutrients · doi:10.3390/nu16091352 · Cited by 62 · see citing works
Davis, L. S., León, B., Bourk, M. J., & Finkler, W. (2020) · Public Understanding of Science · doi:10.1177/0963662520945136 · Cited by 61 · see citing works
Langenberg, B., Janczyk, M., Koob, V., Kliegl, R. M., & Mayer, A. (2022) · Behavior Research Methods · doi:10.3758/s13428-022-01902-8 · Cited by 76 · see citing works
Konuk, F. A., & Otterbring, T. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103531 · Cited by 64 · see citing works
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Pauketat, J. V. T., & Anthis, J. R. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107372 · Cited by 60 · see citing works
Li, Y., & Bates, T. C. (2020) · Intelligence · doi:10.1016/j.intell.2020.101471 · Cited by 62 · see citing works
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Michelini, G., Norman, L. J., Shaw, P., & Loo, S. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02207-2 · Cited by 49 · see citing works
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Giner‐Sorolla, R., Montoya, A. K., Aberson, C. L., Carpenter, T., Lewis, N. A., Bostyn, D. H., Conrique, B. G., Ng, B., Reifman, A. S., Schoemann, A. M., et al. (2023) · doi:10.31234/osf.io/rv3kw · Cited by 62 · see citing works
Yan, Z., King, R. B., & Haw, J. Y. (2021) · Assessment in Education Principles Policy and Practice · doi:10.1080/0969594x.2021.1988510 · Cited by 69 · see citing works
Klein, F., Kohl, S. H., Lührs, M., Mehler, D. M. A., & Sorger, B. (2024) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2023.0087 · Cited by 57 · see citing works
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Gomutbutra, P., Yingchankul, N., Chattipakorn, N., Chattipakorn, S. C., & Srisurapanont, M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02209 · Cited by 52 · see citing works
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Nyhan, B. J., Porter, E. V., & Wood, T. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2122069119 · Cited by 47 · see citing works
Wong, K. T. C., Chan, C. S., Chan, M. Y. H., Wong, C. L. H., Cheng, Q., Xiong, C., & Yip, P. S. F. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.05.056 · Cited by 47 · see citing works
Mesquida, C., Murphy, J., Lakens, D., & Warne, J. P. (2023) · Journal of Sports Sciences · doi:10.1080/02640414.2023.2269357 · Cited by 51 · see citing works
van der Storm, L., Lissa, C. J. V., Lucassen, N., Helmerhorst, K. O. W., & Keizer, R. (2021) · Marriage & Family Review · doi:10.1080/01494929.2021.1927931 · Cited by 50 · see citing works
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Zickfeld, J., van de Ven, N., Pich, O., Schubert, T. W., Berkessel, J. B., Pizarro, J. J., Bhushan, B., Mateo, N. J., Barbosa, S., Sharman, L. S., et al. (2021) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2021.104137 · Cited by 42 · see citing works
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Dong, M., Weststrate, N. M., & Fournier, M. A. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221114096 · Cited by 45 · see citing works
Nissim, N. R., McAfee, D., Edwards, S., Prato, A., Lin, J. X., Lu, Z., Coslett, H. B., & Hamilton, R. H. (2023) · Neuromodulation Technology at the Neural Interface · doi:10.1016/j.neurom.2022.12.014 · Cited by 38 · see citing works
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Herssens, N., Saeys, W., Vereeck, L., Meijer, K., van de Berg, R., Rompaey, V. V., McCrum, C. L., & Hallemans, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-85870-7 · Cited by 37 · see citing works
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Brand, R., & Panteleimon Ekkekakis, A. (2021) · Society for Transparency, Openness, and Replication in Kinesiology eBooks · doi:10.51224/b1004 · Cited by 38 · see citing works
Sommet, N., Weissman, D. L., Cheutin, N., & Elliot, A. (2022) · doi:10.31219/osf.io/xhe3u · Cited by 36 · see citing works
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Gómez‐Polo, C., Casado, A. M. M., & Montero, J. (2022) · Journal of Dentistry · doi:10.1016/j.jdent.2022.104143 · Cited by 42 · see citing works
Melkonian, M., McDonald, S., Scott, A. J., Karin, E., Dear, B. F., & Wootton, B. M. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.08.037 · Cited by 37 · see citing works
Edelsbrunner, P. A., & Thurn, C. (2023) · Educational Research Review · doi:10.1016/j.edurev.2023.100590 · Cited by 44 · see citing works
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Clark, O. J., Delgado-Sánchez, A., Cullell, N., Corrêa, S. A. L., Krupiński, J., & Ray, N. J. (2024) · Sleep Medicine · doi:10.1016/j.sleep.2024.05.007 · Cited by 36 · see citing works
Taylor, R. W., Haszard, J. J., Healey, D. M., Meredith-Jones, K. A., Taylor, B. J., & Galland, B. C. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01185-w · Cited by 37 · see citing works
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Muñoz‐Tamayo, R., Nielsen, B. L., Gagaoua, M., Gondret, F., Krause, E. T., Morgavi, D. P., Olsson, I. A. S., Pastell, M., Taghipoor, M., Tedeschi, L. O., et al. (2022) · PNAS Nexus · doi:10.1093/pnasnexus/pgac106 · Cited by 36 · see citing works
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Duplenne, L., Bourdin, B., Fernandez, D., Blondelle, G., & Aubry, A. (2023) · Gifted Child Quarterly · doi:10.1177/00169862231208922 · Cited by 46 · see citing works
Luthar, S. S., Ebbert, A. M., & Kumar, N. L. (2021) · American Psychologist · doi:10.1037/amp0000764 · Cited by 36 · see citing works
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Franz, D. J., Richter, T., Lenhard, W., Marx, P., Stein, R., & Ratz, C. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09716-6 · Cited by 35 · see citing works
Caldwell, D. M., Davies, S. R., Thorn, J. C., Palmer, J. C., Caro, P., Hetrick, S. E., Gunnell, D., Anwer, S., López-López, J. A., French, C. E., et al. (2021) · Public Health Research · doi:10.3310/phr09080 · Cited by 37 · see citing works
Vuogan, A., & Li, S. (2023) · Applied Linguistics Review · doi:10.1515/applirev-2022-0192 · Cited by 35 · see citing works
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Vaidis, D. C., Sleegers, W. W. A., van Leeuwen, F., DeMarree, K. G., Sætrevik, B., Ross, R. M., Schmidt, K., Protzko, J., Morvinski, C., Ghasemi, O., et al. (2024) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459231213375 · Cited by 34 · see citing works
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Govers, J., Velloso, E., Kostakos, V., & Gonçalves, J. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642322 · Cited by 34 · see citing works
- Authors
- Schäfer, T., & Schwarz, M. A.
- Affiliations
- Chemnitz University of Technology (DE)
- Corresponding author
- Schäfer, Thomas
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2019-04-11
- Volume
- 10
- Pages
- 813-813
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC6470248
- OpenAlex
- W2937326640
- Cited by
- 774
- References
- 43
- Citations by year
- 2026: 73 · 2025: 105 · 2024: 101 · 2023: 123 · 2022: 149 · 2021: 127 · 2020: 75 · 2019: 18 · 2018: 1 · 2017: 1
- FWCI
- 61.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Qucosa (Saxon State and University Library Dresden) (submittedVersion, cc-by)
- Funders
- Technische Universität Chemnitz
- Deutsche Forschungsgemeinschaft
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- effect size, Cohen's d, publication bias, questionable research practices, preregistration, effect size inflation, statistical power
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