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Using Effect Size—or Why the P Value Is Not Enough
Open accessAbstract
These statements about the importance of effect sizes were made by two of the most influential statistician-researchers of the past half-century. Yet many submissions to Journal of Graduate Medical Education omit mention of the effect size in quantitative studies while prominently displaying the P value. In this paper, we target readers with little or no statistical background in order to encourage you to improve your comprehension of the relevance of effect size for planning, analyzing, reporting, and understanding education research studies.In medical education research studies that compare different educational interventions, effect size is the magnitude of the difference between groups. The absolute effect size is the difference between the average, or mean, outcomes in two different intervention groups. For example, if an educational intervention resulted in the improvement of subjects' examination scores by an average total of 15 of 50 questions as compared to that of another intervention, the absolute effect size is 15 questions or 3 grade levels (30%) better on the examination. Absolute effect size does not take into account the variability in scores, in that not every subject achieved the average outcome.In another example, residents' self-assessed confidence in performing a procedure improved an average of 0.4 point on a Likert-type scale ranging from 1 to 5, after simulation training. While the absolute effect size in the first example appears clear, the effect size in the second example is less apparent. Is a 0.4 change a lot or trivial? Accounting for variability in the measured improvement may aid in interpreting the magnitude of the change in the second example.Thus, effect size can refer to the raw difference between group means, or absolute effect size, as well as standardized measures of effect, which are calculated to transform the effect to an easily understood scale. Absolute effect size is useful when the variables under study have intrinsic meaning (eg, number of hours of sleep). Calculated indices of effect size are useful when the measurements have no intrinsic meaning, such as numbers on a Likert scale; when studies have used different scales so no direct comparison is possible; or when effect size is examined in the context of variability in the population under study.Calculated effect sizes can also quantitatively compare results from different studies and thus are commonly used in meta-analyses.The effect size is the main finding of a quantitative study. While a P value can inform the reader whether an effect exists, the P value will not reveal the size of the effect. In reporting and interpreting studies, both the substantive significance (effect size) and statistical significance (P value) are essential results to be reported.For this reason, effect sizes should be reported in a paper's Abstract and Results sections. In fact, an estimate of the effect size is often needed before starting the research endeavor, in order to calculate the number of subjects likely to be required to avoid a Type II, or β, error, which is the probability of concluding there is no effect when one actually exists. In other words, you must determine what number of subjects in the study will be sufficient to ensure (to a particular degree of certainty) that the study has acceptable power to support the null hypothesis. That is, if no difference is found between the groups, then this is a true finding.Statistical significance is the probability that the observed difference between two groups is due to chance. If the P value is larger than the alpha level chosen (eg, .05), any observed difference is assumed to be explained by sampling variability. With a sufficiently large sample, a statistical test will almost always demonstrate a significant difference, unless there is no effect whatsoever, that is, when the effect size is exactly zero; yet very small differences, even if significant, are often meaningless. Thus, reporting only the significant P value for an analysis is not adequate for readers to fully understand the results.For example, if a sample size is 10 000, a significant P value is likely to be found even when the difference in outcomes between groups is negligible and may not justify an expensive or time-consuming intervention over another. The level of significance by itself does not predict effect size. Unlike significance tests, effect size is independent of sample size. Statistical significance, on the other hand, depends upon both sample size and effect size. For this reason, P values are considered to be confounded because of their dependence on sample size. Sometimes a statistically significant result means only that a huge sample size was used.3A commonly cited example of this problem is the Physicians Health Study of aspirin to prevent myocardial infarction (MI).4 In more than 22 000 subjects over an average of 5 years, aspirin was associated with a reduction in MI (although not in o
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“Concerning effect size, the r-value was 0.34.This would be counted as medium effect size (Sullivan & Feinn, 2012).”
From Teaching and Learning Science Using YouTube Videos and Discovery Learning in Primary School (2020) · cites this paper as Sullivan & Feinn, 2012
Experimental — accuracy not yet measuredIn the citing paper
“effect sizes, however, are independent of sample size (Sullivan and Feinn, 2012).”
From A chatbot-delivered intervention for optimizing social media use and reducing perceived isolation among rural-living LGBTQ+ youth: Development, acceptability, usability, satisfaction, and utility (2023) · cites this paper as Sullivan and Feinn, 2012
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- Coe R. It's the effect size, stupid: what “effect size” is and why it is important. Paper presented at the 2002 Annual Conference of the British Educational Research Association, University of Exeter, Exeter, Devon, England, September 12–14, 2002. http://www.leeds.ac.uk/educol/documents/00002182.htm. Accessed March 23, 2012.
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“…nominal variable and a continuous variable) and Spearman’s rank-order correlation (between ordinal and continuous variables or between two continuous variables) measured the strength of the relationship between two variables and the direction of the relationship (Sullivan & Feinn, 2012).”
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“26 The LME model, the slope comparisons, and the false discovery rate P value adjustments were calculated in R using the lme4, emmeans , and stats packages, respectively.”
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“The effect size expressed as Cohen’s d was 1.246, which is considered large 31 .”
InfluentialMurtha, K. A., Dorfschmidt, L., Bethlehem, R. A. I., Kang, K., Vandekar, S., Alexander-Bloch, A. F., Waller, R. E., & Seidlitz, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.23.655740 · Cited by 1
“Second, sample size differed significantly across dimensional, tail-sampled, and propensity matched groups, which could have contributed to differences in statistical significance across modeling strategies (Sullivan & Feinn, 2012).”
Krishnan, K., Tan, L.-F., Ng, D., & Krishnan, P. (2025) · Open Biomedical Engineering Journal · doi:10.2174/0118741207372787250515052702 · Cited by 1
Efficacy of plantar vibration on balance and postural control post-stroke: A systematic review
Coles, H. J. (2025) · The journal of the International Society of Physical and Rehabilitation Medicine · doi:10.1097/ph9.0000000000000078 · Cited by 1
Injuries in the cervical craniomandibular complex after whiplash phenomenon
Ron, B., Perez, P. A., Almedariz, M. V., Rodriguez-Tates, M., Bedón, A. G., Ortíz-Prado, E., & Chauca-Bajaña, L. (2025) · European Journal of Medical Research · doi:10.1186/s40001-025-02537-z · Cited by 1
“In addition to bias issues, retrospective studies generally inquire only about trauma injuries (cervix/cranial/mandibular, whiplash) [15], overlooking potential injuries to routine jaw function (e.g., prolonged mouth opening, subluxation, dislocation) [16].”
InfluentialNeuropsychiatric changes following striatal stroke– results from the observational PostPsyDis study
Kufner, A., Rios, A. S., Winter, B., Temuulen, U., Khalil, A., Grittner, U., Schöner, J., Akdeniz, A., Lachmann, U., Kronenberg, G., et al. (2025) · Neurological Research and Practice · doi:10.1186/s42466-025-00390-3 · Cited by 1
“This estimate was based on Cohen’s conventional effect size guidelines and literature suggesting moderate associations between lesion location and post-stroke affective outcomes [12, 13, 14].”
Vieira, A., Blanco‐Rambo, E., Bandeira‐Guimarães, M., Silva, R. T., Fergutz, A., Paz, I. D. A., Munhoz, S. V., Colombelli, R. A. W., Vaz, M. A., Macedo, R. C. O., et al. (2025) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.2024-0215 · Cited by 2
Whole-body vibration transmission during resistance vibration exercise
Sorrentino, R. G., Verdel, N., Supej, M., Ciuha, U., & Mekjavić, I. B. (2025) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2025.1573571 · Cited by 1
Rojas-Rodríguez, G., Meza-Colín, J., Munro, A., García-Moreno, T., Morales-Hernández, F., Virgen-Ortíz, J., Salvador-Hernández, J. L., Rodríguez-García, G., del Río, R. D., Ramírez-Briones, E., et al. (2025) · Revista Brasileira de Botânica · doi:10.1007/s40415-025-01081-8 · Cited by 1
“According to the data presented, it is observed that the calculated effect size for the interaction between groups in the various ANOVA tests is at an average value according to Cohen’s index (Sullivan and Feinn 2012), as shown in the supplementary information.”
Imphat, C., Woottisin, N., & Chiewsilp, W. (2025) · Journal of Ayurveda and Integrative Medicine · doi:10.1016/j.jaim.2024.101108 · Cited by 1
“There was no significant difference between ZR spray and DF spray in the mean changes of walking time from baseline to the 1st and 2nd visits, with an effect size of less than 0.2 (Table 3), indicating a small effect [24].”
InfluentialDumanli, D., & Şeker, Ç. (2025) · Diagnostics · doi:10.3390/diagnostics15091160 · Cited by 1
“However, considering that thresholds of 0.10, 0.30, and 0.70 are specifically recommended for studies on the temporomandibular joint (TMJ) and masticatory muscles, these adjusted values were adopted as reference points for interpreting the results in these studies [14,15].”
Influentialde la Calva, C., Angulo, M., González-Rojo, P., Peiró, A., Machado, P., Cebrián, J. L., García-Maroto, R., Valcárcel, A., Puertas, P., Valero-Cifuentes, G., et al. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14093242 · Cited by 1
“Cohen’s d statistic was calculated to estimate the effect size of the comparative analyses for continuous variables [16].”
The Impact of the COVID-19 Pandemic on Children and Adolescents with ADHD
Segal, H., Shachar‐Lavie, I., Bar-David, I., Fennig, S., & Benaroya-Milshtein, N. (2025) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2025.05.003 · Cited by 1
Chun, J., Liu, Y., Kibler, G. L., Lee, H., Babakhani, K., Rhoades, N., Bivins, I., Ko, J., Dickerson, B., Gonzalez, D. E., et al. (2026) · Journal of the International Society of Sports Nutrition · doi:10.1080/15502783.2026.2716273
“Additionally, it provides an assessment of the clinical significance of findings [88,91–96].”
Syahril, S., Wulansari, R. E., Safitri, D., Syahri, B., Kiong, T. T., Fortuna, A., & Nabawi, R. A. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.103636
Liu, D., Wang, Y., Iu, H. C., Zhang, L., Shi, C., Lu, Y., & Ma, X. (2026) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3830398.3830658
“Expert-evaluated prematureness used Wilcoxon Signed-Rank tests for paired comparisons, reporting test statistics, 𝑝 -values, and effect sizes throughout [50, 53, 54].”
Bezmalinovic, A., Brito, E., Rivera, E., Godoy‐Guzmán, C., García‐Herrera, C., Celentano, D. J., & Herrera, E. A. (2026) · International Journal of Engineering Science · doi:10.1016/j.ijengsci.2026.104642
Li, X., Huang, Q., Wang, F.-Y., Sheng, Y., & Wang, B. (2026) · Food Research International · doi:10.1016/j.foodres.2026.120350
Verrills, P., Mohabbati, V., Yu, J., Green, M. D. S., Bates, D., Mihailidis, H., & Russo, M. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15218389
Mensah, I. K., & Khan, M. K. (2026) · Current Psychology · doi:10.1007/s12144-026-10222-5
“…effect size of the GC is not harmful, as large samples can yield statistically significant small effects that may still hold practical importance, especially in medical, educational, and social sciences fields, where small effects can lead to substantial consequences (Sullivan & Feinn, 2012 ).”
Luo, R.-H., Guo, S.-X., & Bocklitz, T. (2026) · Bioengineering · doi:10.3390/bioengineering13111257
Song, H., Shin, M., Choi, J., Kim, Y., Jang, K., Suh, B., & Jung, H. (2026) · Proceedings of the 2026 28th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3797867.3828985
“…(Cliff’s delta) rather than relying solely on statistical significance; effect sizes quantify the magnitude of differences independent of sample size, which matters when small samples may lack the statistical power to detect practically meaningful effects through significance testing alone [50].”
Augello, M., & Mafrolla, E. (2026) · Journal of Applied Accounting Research · doi:10.1108/jaar-08-2025-0446
Vural, N., Duyan, M., Ertaş, E., Guven, H., Akçimen, M., & Unal, O. G. (2026) · Sao Paulo medical journal = Revista paulista de medicina · doi:10.1590/1516-3180.2026.3603.14082026
Iavich, M., Kuchukhidze, T., & Lopata, A. (2026) · Symmetry · doi:10.3390/sym18111768
Sarnaik, D., Sullivan, C., Krishnakumar, A., Chen, F., Organski, A. C., Campbell, W. W., Johnson, J. R., Cross, T.-W., & Rahimi, R. (2026) · Advanced Materials Technologies · doi:10.1002/admt.71389
Coupling Raman Spectroscopy and Acoustic Microscopy to Characterize Glioblastoma Resistance
Pesen, T., Inanc, A., Inci, D., Cingoz, A., & Akgün, B. (2026) · bioRxiv · doi:10.64898/2026.10.14.759182
“8b (33).”
Sari, S. P., Bunawan, W., & Surya, E. (2026) · International Journal of Education and Practice · doi:10.18488/61.v14i4.5255
“This analysis will provide the mean difference, 95% c onfidence interval, and Cohen’s dz to assess the magnitude of change (Lakens, 2013; Sullivan & Feinn, 2012).”
Kalyani, H. H., Sullivan, K., Moyle, G., Brauer, S., Jeffrey, E. R., & Kerr, G. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1962191
“Cohen’s d were interpreted according to recommended standards (small = 0.2, medium = 0.5, large = 0.8) (Sullivan and Feinn, 2012).”
InfluentialPuerta-Zapata, J., Orozco, E. C. S., Osorio, C. E., Triana, V. Y., Ruiz, M. A., & Gómez-Velásquez, S. (2026) · Población y Salud en Mesoamérica · doi:10.15517/3dfx2846
“El tamaño del efecto fue moderado y significativo (r biserial = 0,53; IC 95 % [0,43 – 0,61]), lo que confirma una reducción estadística y clínicamente relevante en la severidad de las estrategias de afrontamiento utilizadas por los hogares (Sullivan & Feinn, 2012).”
Salek, S., Johns, J., Ali, F., Dalgard, F., Kupfer, J., & Finlay, A. (2026) · Archives of Dermatological Research · doi:10.1007/s00403-026-04877-0
“Group differences are then determined using a statistical test and the effect size can also be determined [56].”
Lipid Profile Abnormalities In Patients With Metabolic Syndrome; a Case Control Study
Rai, S., Devi, K., Savita, K., Yadav, N., & Nigoshkar, S. (2026) · International Journal of Drug Delivery Technology · doi:10.25258/ijddt.16.65s.103
Metadata
- Authors
- Sullivan, G. M., & Feinn, R.
- Affiliations
- University of Connecticut (US)
- Corresponding author
- Sullivan, Gail M.
- Venue
- Journal of Graduate Medical Education
- Published
- 2012-09
- Volume
- 4
- Issue
- 3
- Pages
- 279-282
- ISSN
- 1949-8349 (ISSN-L)
- 1949-8357
- PMC
- PMC3444174
- OpenAlex
- W2107026277
- Cited by
- 5,553
- References
- 6
- Citations by year
- 2026: 607 · 2025: 877 · 2024: 759 · 2023: 547 · 2022: 574 · 2021: 499 · 2020: 416 · 2019: 419 · 2018: 320 · 2017: 222 · 2016: 215 · 2015: 83 · 2014: 9 · 2013: 4 · 2012: 2
- FWCI
- 35.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Graduate Medical Education (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Education › Educational Research and Methods
- Keywords
- effect size, p-values, statistical significance, substantive significance, standardized mean difference, medical education research, educational intervention, meta-analysis, simulation-based training, resident confidence, test scores, interpretation of study results, graduate medical education, reporting guidelines
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