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On effect size.
Abstract
The call for researchers to report and interpret effect sizes and their corresponding confidence intervals has never been stronger. However, there is confusion in the literature on the definition of effect size, and consequently the term is used inconsistently. We propose a definition for effect size, discuss 3 facets of effect size (dimension, measure/index, and value), outline 10 corollaries that follow from our definition, and review ideal qualities of effect sizes. Our definition of effect size is general and subsumes many existing definitions of effect size. We define effect size as a quantitative reflection of the magnitude of some phenomenon that is used for the purpose of addressing a question of interest. Our definition of effect size is purposely more inclusive than the way many have defined and conceptualized effect size, and it is unique with regard to linking effect size to a question of interest. Additionally, we review some important developments in the effect size literature and discuss the importance of accompanying an effect size with an interval estimate that acknowledges the uncertainty with which the population value of the effect size has been estimated. We hope that this article will facilitate discussion and improve the practice of reporting and interpreting effect sizes.
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Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials
the CONSORT Group, Schulz, K. F., Altman, D. G., & Moher, D. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-18 · Cited by 13,371
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
Self-citationPreacher, K. J., & Kelley, K. (2011) · Psychological Methods · doi:10.1037/a0022658 · Cited by 3,060
Self-citationDes Jarlais, D. C., Lyles, C., Crepaz, N., & the TREND Group (2004) · American Journal of Public Health · doi:10.2105/ajph.94.3.361 · Cited by 2,817
Statistical methods in psychology journals: Guidelines and explanations.
Wilkinson, L., & Task Force on Statistical Inference (1999) · American Psychologist · doi:10.1037/0003-066x.54.8.594 · Cited by 2,791
Ellis, P. D. (2010) · doi:10.1017/cbo9780511761676 · Cited by 2,461
Effect Sizes for Interpreting Changes in Health Status
Kazis, L. E., Anderson, J. J., & Meenan, R. F. (1989) · Medical Care · doi:10.1097/00005650-198903001-00015 · Cited by 2,401
Publication Bias in Meta‐Analysis: Prevention, Assessment and Adjustments
(2005) · doi:10.1002/0470870168 · Cited by 2,368
Cited by
Statistical mediation analysis with a multicategorical independent variable
Hayes, A. F., & Preacher, K. J. (2014) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12028 · Cited by 3,403
Self-citationHayes, A. F., & Rockwood, N. J. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.11.001 · Cited by 2,350
Un sistema de clasificación de los diseños de investigación en psicología
Ato, M., López-García, J. J., & Benavente, A. (2013) · Anales de Psicología · doi:10.6018/analesps.29.3.178511 · Cited by 2,254
Lakens, D. (2022) · Collabra Psychology · doi:10.1525/collabra.33267 · Cited by 1,962
How Big Is “Big”? Interpreting Effect Sizes in L2 Research
Plonsky, L., & Oswald, F. L. (2014) · Language Learning · doi:10.1111/lang.12079 · Cited by 1,960
Interpreting effect sizes of education interventions
Kraft, M. A. (2020) · Educational Researcher · doi:10.3102/0013189x20912798 · Cited by 1,281
Schäfer, T., & Schwarz, M. A. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00813 · Cited by 774
Correlational effect size benchmarks
Bosco, F. A., Aguinis, H., Singh, K., Field, J. G., & Pierce, C. A. (2015) · Journal of Applied Psychology · doi:10.1037/a0038047 · Cited by 768
Kim, J.-H. (2018) · Journal of Travel Research · doi:10.1177/0047287517721369 · Cited by 679
Effect size measures for multilevel models: definition, interpretation, and TIMSS example
Lorah, J. (2018) · Large-scale Assessments in Education · doi:10.1186/s40536-018-0061-2 · Cited by 650
Systematic review and meta-analysis of augmented reality in educational settings
Garzón, J., Pavón, J., & Baldiris, S. (2019) · Virtual Reality · doi:10.1007/s10055-019-00379-9 · Cited by 562
An automated essay scoring systems: a systematic literature review
Ramesh, D., & Sanampudi, S. K. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-021-10068-2 · Cited by 550
Meta-analysis of the impact of Augmented Reality on students’ learning gains
Garzón, J., & Acevedo, J. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.04.001 · Cited by 491
Chapman, C. R., & Vierck, C. J. (2017) · The Journal of Pain · doi:10.1016/j.jpain.2016.11.004 · Cited by 423
Rights, J. D., & Sterba, S. K. (2019) · Psychological Methods · doi:10.1037/met0000184 · Cited by 413
Anderson, S. F., Kelley, K., & Maxwell, S. E. (2017) · Psychological Science · doi:10.1177/0956797617723724 · Cited by 406
Self-citationHeterogeneity in ecological and evolutionary meta‐analyses: its magnitude and implications
Senior, A. M., Grueber, C. E., Kamiya, T., Lagisz, M., O'Dwyer, K., Santos, E. S. A., & Nakagawa, S. (2016) · Ecology · doi:10.1002/ecy.1591 · Cited by 299
A novel measure of effect size for mediation analysis
Lachowicz, M. J., Preacher, K. J., & Kelley, K. (2018) · Psychological Methods · doi:10.1037/met0000165 · Cited by 271
Self-citationKelley, K., & Pornprasertmanit, S. (2016) · Psychological Methods · doi:10.1037/a0040086 · Cited by 259
Self-citationGreenberg, M. T., & Abenavoli, R. (2017) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2016.1246632 · Cited by 255
Beyond linear mediation: Toward a dynamic network approach to study treatment processes
Hofmann, S. G., Curtiss, J. E., & Hayes, S. C. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101824 · Cited by 232
Explained variance measures for multilevel models
LaHuis, D. M., Hartman, M. J., Hakoyama, S., & Clark, P. C. (2014) · Organizational Research Methods · doi:10.1177/1094428114541701 · Cited by 239
Lewis, K. L., Stout, J. G., Finkelstein, N. D., Pollock, S. J., Miyake, A., Cohen, G. L., & Ito, T. A. (2017) · Psychology of Women Quarterly · doi:10.1177/0361684317720186 · Cited by 224
Pakenham, K. I., Landi, G., Boccolini, G., Furlani, A., Grandi, S., & Tossani, E. (2020) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2020.07.003 · Cited by 210
Practical recommendations to conduct a neuroimaging meta-analysis for neuropsychiatric disorders
Tahmasian, M., Sepehry, A. A., Samea, F., Khodadadifar, T., Soltaninejad, Z., Javaheripour, N., Khazaie, H., Zarei, M., Eickhoff, S. B., & Eickhoff, C. R. (2019) · Human Brain Mapping · doi:10.1002/hbm.24746 · Cited by 126
Hofstede’s cultural dimensions in technology acceptance models: a meta-analysis
Jan, J., Alshare, K. A., & Lane, P. L. (2024) · Universal Access in the Information Society · doi:10.1007/s10209-022-00930-7 · Cited by 127
Baenas, I., Caravaca‐Sanz, E., Granero, R., Sánchez, I., Riesco, N., Testa, G., Vintró‐Alcaraz, C., Treasure, J., Jiménez‐Murcia, S., & Fernández‐Aranda, F. (2020) · European Eating Disorders Review · doi:10.1002/erv.2771 · Cited by 102
Warthon-Medina, M., Moran, V. H., Stammers, A.-L., Dillon, S., Qualter, P., Nissensohn, M., Serra-Majem, L., & Lowe, N. M. (2015) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2015.60 · Cited by 96
Agorastos, A., Boel, J. A., Heppner, P. S., Hager, T., Moeller-Bertram, T., Haji, U., Motazedi, A., Yanagi, M. A., Baker, D. G., & Stiedl, O. (2013) · Stress · doi:10.3109/10253890.2012.751369 · Cited by 88
Fernández‐Aranda, F., Munguía, L., Mestre‐Bach, G., Steward, T., Etxandi, M., Baenas, I., Granero, R., Sánchez, I., Ortega, E., Andreu, A., et al. (2020) · European Eating Disorders Review · doi:10.1002/erv.2784 · Cited by 74
Factors influencing waiting times for diagnosis of Autism Spectrum Disorder in children and adults
McKenzie, K., Forsyth, K., O’Hare, A., McClure, I., Rutherford, M., Murray, A., & Irvine, L. (2015) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2015.07.033 · Cited by 51
Mallorquí-Bagué, N., Mena-Moreno, T., Granero, R., Vintró-Alcaraz, C., Sánchez-González, J., Fernández-Aranda, F., Pino-Gutiérrez, A. D., Mestre-Bach, G., Aymamí, N., Gómez-Peña, M., et al. (2018) · Journal of Behavioral Addictions · doi:10.1556/2006.7.2018.132 · Cited by 39
Lozano-Madrid, M., Clark Bryan, D., Granero, R., Sánchez, I., Riesco, N., Mallorquí-Bagué, N., Jiménez-Murcia, S., Treasure, J., & Fernández-Aranda, F. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9061936 · Cited by 38
Armon, G., Melamed, S., Shirom, A., Berliner, S., & Shapira, I. (2013) · Personality and Individual Differences · doi:10.1016/j.paid.2012.11.035 · Cited by 54
Feingold, A. (2019) · The Quantitative Methods for Psychology · doi:10.20982/tqmp.15.2.p096 · Cited by 34
McArthur, B. A., Browne, D., Racine, N., Tough, S., & Madigan, S. (2022) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-021-00895-w · Cited by 26
Brand, A., & Bradley, M. T. (2016) · Psychological Reports · doi:10.1177/0033294115625265 · Cited by 25
Subtyping treatment-seeking gaming disorder patients
Granero, R., Fernández-Aranda, F., Castro-Calvo, J., Billieux, J., Valero-Solís, S., Mora-Maltas, B., Rivas-Pérez, S., Valenciano-Mendoza, E., del Pino-Gutiérrez, A., Gómez-Peña, M., et al. (2021) · Addictive Behaviors · doi:10.1016/j.addbeh.2021.107086 · Cited by 23
The somatic molecular evolution of cancer: Mutation, selection, and epistasis
Dasari, K., Somarelli, J. A., Kumar, S., & Townsend, J. P. (2021) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2021.08.003 · Cited by 22
Kurz, A. S., Bethay, J. S., & Ladner-Graham, J. M. (2014) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2014.06.003 · Cited by 21
APOLLO: A GPT-based tool to detect phishing emails and generate explanations that warn users
Desolda, G., Greco, F., & Vigano, L. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3733049 · Cited by 16
Joint Hypermobility Classes in 9-Year-Old Children from the General Population and Anxiety Symptoms
Ezpeleta, L., Navarro, J. B., Osa, N. D. L., Penelo, E., & Bulbena, A. (2018) · Journal of Developmental & Behavioral Pediatrics · doi:10.1097/dbp.0000000000000577 · Cited by 13
Lo, C.-S., Chen, K.-C., Shih, J.-C., Cheng, B., & Chao, W.-C. (2025) · Journal of Sports Sciences · doi:10.1080/02640414.2025.2534224 · Cited by 12
Single-Cell Transcriptomes Reveal Characteristics of MicroRNAs in Gene Expression Noise Reduction
Hu, T., Wei, L., Li, S., Cheng, T., Zhang, X., & Wang, X. (2021) · Genomics, Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.05.002 · Cited by 12
Metadata
- Authors
- Kelley, K., & Preacher, K. J.
- Venue
- Psychological Methods
- Published
- 2012
- Volume
- 17
- Issue
- 2
- Pages
- 137-152
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2154516913
- Cited by
- 994
- References
- 13
- FWCI
- 42.10
- Type
- journal article
- Language
- en
- Open access
- closed
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