Cited by 474Meta-analysis and systematic reviewsPsychology Research and BibliometricsStatistical Methods and Bayesian Inference

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Effect Sizes for Research

Grissom, Robert J., Kim, John J.·2012·Routledge eBooks

DOI 10.4324/9780203803233

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Abstract

Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their application, interpretation, and limitations. Noted for its practical approach, the book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided. The book's broad disciplinary appeal results from its inclusion of a variety of examples from psychology, medicine, education, and other social sciences. Special attention is paid to confidence intervals, the statistical assumptions of the methods, and robust estimators of effect sizes. The extensive reference section is appreciated by all. With more than 40% new material, highlights of the new editon include: three new multivariate chapters covering effect sizes for analysis of covariance, multiple regression/correlation, and multivariate analysis of variance more learning tools in each chapter including introductions, summaries, "Tips and Pitfalls" and more conceptual and computational questions more coverage of univariate effect sizes, confidence intervals, and effect sizes for repeated measures to reflect their increased use in research more software references for calculating effect sizes and their confidence intervals including SPSS, SAS, R, and S-Plus the data used in the book are now provided on the web along with new data and suggested calculations with IBM SPSS syntax for computational practice. Effect Sizes for Research covers standardized and unstandardized differences between means, correlational measures, strength of association, and parametric and nonparametric measures for between- and within-groups data. Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is also an excellent supplement for advanced statistics courses in psychology, education, the social sciences, business, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.

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Background
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Background
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Method
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Background
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“It is also important to bear in mind that the effect sizes and their confidence intervals derived from zero-order analyses are reliable only when certain conditions are met, specifically normality and homoscedasticity and independence (see Grissom and Kim 2012 and Wilcox 2012 for an introduction).”
Background
Quantifying Soil Erosion from Hiking Trail in a Protected Natural Area in the Spanish Pyrenees
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“To this end, we calculated the epsilonsquared (E2RÞ estimate of effect size, which depends on the value H obtained in the Kruskal–Wallis test and the total number (n) of observations (Grissom & Kim, 2012).”
Method
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“We additionally quantified the effect size by means of the standardized mean difference [38].”
Method
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The Impact of APA and AERA Guidelines on effect size reporting
Peng, C.-Y. J., Chen, L.-T., Chiang, H.-M., & Chiang, Y.-C. (2013) · Educational Psychology Review · doi:10.1007/s10648-013-9218-2 · Cited by 46
I’m not the person I used to be: The self and autobiographical memories of immoral actions.
Stanley, M. L., Henne, P., Iyengar, V., Sinnott-Armstrong, W. P., & Brigard, F. D. (2017) · Journal of Experimental Psychology General · doi:10.1037/xge0000317 · Cited by 46
“To assess effect sizes, we used PSdep (Grissom & Kim, 2012), which is the probability that in a randomly sampled pair of scores, the score from one condition (the condition which most frequently has the higher score) will be greater than the score from the other condition (the condition which most…”
MethodInfluential
Beyond “sex prediction”: Estimating and interpreting multivariate sex differences and similarities in the brain
Sanchis‐Segura, C., Aguirre, N., Cruz-Gómez, Á. J., Félix, S., & Forn, C. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119343 · Cited by 48
Métodos estadísticos para el análisis del tamaño del efecto
Macías, M. E. R., Zarco-Villavicencio, I. S., & Villasís-Keever, M. Á. (2021) · Revista Alergia México · doi:10.29262/ram.v658i2.949 · Cited by 60
Assisted closed-loop optimization of SSVEP-BCI efficiency
Fernández-Vargas, J., Pfaff, H. U., Rodrı́guez, F. B., & Varona, P. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2013.00027 · Cited by 46
Comparison of progressive addition lenses for general purpose and for computer vision: an office field study
Jaschinski, W., König, M., Mekontso, T. M., Ohlendorf, A., & Welscher, M. (2015) · Clinical and Experimental Optometry · doi:10.1111/cxo.12259 · Cited by 45
Is alliteration mnemonic without awareness-raising?
Boers, F., Lindstromberg, S., & Eyckmans, J. (2013) · Language Awareness · doi:10.1080/09658416.2013.774008 · Cited by 49
“In behavioural and educational studies a d-value as high as 0.88 certainly qualifies as substantive (e.g. Grissom & Kim, 2012, pp. 128–130).”
BackgroundInfluential
Cohen’s d needs to be readily interpretable: Comment on Shieh (2013)
Cumming, G. (2013) · Behavior Research Methods · doi:10.3758/s13428-013-0392-4 · Cited by 44
Preliminary evaluation of a brief mindfulness-based stress reduction intervention for mental health professionals
Dobie, A., Tucker, A., Ferrari, M., & Rogers, J. M. (2016) · Australasian Psychiatry · doi:10.1177/1039856215618524 · Cited by 43
On automatically detecting similar Android apps
Linares-Vasquez, M., Holtzhauer, A., & Poshyvanyk, D. (2016) · 2016 IEEE 24th International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2016.7503721 · Cited by 43
“We followed the guidelines in [27] to interpret the effect size values: negligible for |d| < 0.”
Method
Demystifying Prediction in Mediation Research and the Use of Specific Indirect Effects and Indirect Effect Sizes
Gaskin, J. E., Ogbeibu, S., & Lowry, P. B. (2023) · Springer eBooks · doi:10.1007/978-3-031-37772-3_8 · Cited by 55
Effects of intra‐articular hyaluronic acid associated to Chitlac (arty‐duo®) in a rat knee osteoarthritis model
Salamanna, F., Giavaresi, G., Parrilli, A., Martini, L., Aldini, N. N., Abatangelo, G., Frizziero, A., & Fini, M. (2019) · Journal of Orthopaedic Research® · doi:10.1002/jor.24259 · Cited by 42
Does the type of foam roller influence the recovery rate, thermal response and DOMS prevention?
Adamczyk, J. G., Gryko, K., & Boguszewski, D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235195 · Cited by 43
Quality of implementation of a school mental health initiative and changes over time in students’ social and emotional competencies
Askell‐Williams, H., Dix, K., Lawson, M. J., & Slee, P. T. (2012) · School Effectiveness and School Improvement · doi:10.1080/09243453.2012.692697 · Cited by 50
“Similarly, Grissom and Kim (2012) stated, ‘‘The designations of small, medium and large effect sizes do not necessarily correspond to the degree of practical or theoretical significance of an effect’’ (p. 130), arguing that small but consistent effects can have considerable impact over time.”
Background
Mechanical and in vitro biological properties of uniform and graded Cobalt‐chrome lattice structures in orthopedic implants
Pagani, S., Liverani, E., Giavaresi, G., Luca, A. D., Belvedere, C., Fortunato, A., Leardini, A., Fini, M., Tomesani, L., & Caravaggi, P. (2021) · Journal of Biomedical Materials Research Part B Applied Biomaterials · doi:10.1002/jbm.b.34857 · Cited by 42
Faking ADHD? Symptom Validity Testing and Its Relation to Self-Reported, Observer-Reported Symptoms, and Neuropsychological Measures of Attention in Adults With ADHD
Hirsch, O., & Christiansen, H. (2015) · Journal of Attention Disorders · doi:10.1177/1087054715596577 · Cited by 44
“The size of the resulting effects was examined with the effect sizes probability of superiority (PS) and eta2 (Grissom & Kim, 2012).”
Method
The New Statistics: A How‐To Guide
Cumming, G. (2013) · Australian Psychologist · doi:10.1111/ap.12018 · Cited by 46
A Multi‐Method Study of the Geriatric Learning Needs of Acute Care Hospital Nurses in Ontario, Canada
Fox, M. T., Butler, J. I., Persaud, M., Tregunno, D., Sidani, S., & McCague, H. (2015) · Research in Nursing & Health · doi:10.1002/nur.21699 · Cited by 39
Motivation for Psychotherapy and Illness Beliefs in Turkish Immigrant Inpatients in Germany: Results of a Cultural Comparison Study
Reich, H., Bockel, L., & Mewes, R. (2014) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-014-0054-y · Cited by 39
“, estimating the “pure” contribution [59].”
Method
Outcomes of an Advanced Ultrasound Elective
Prats, M. I., Royall, N. A., Panchal, A. R., et al. (2016) · Journal of Ultrasound in Medicine · doi:10.7863/ultra.15.06060 · Cited by 39
Effects of Visual Aids for End-of-Life Care on Decisional Capacity of People With Dementia
Chang, W.-Z. D., & Bourgeois, M. S. (2019) · American Journal of Speech-Language Pathology · doi:10.1044/2019_ajslp-19-0028 · Cited by 39
Learning-oriented e-assessment: the effects of a training and guidance programme on lecturers’ perceptions
Gómez, G. R., Serra, V. Q., & Sáiz, M. S. I. (2014) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2014.979132 · Cited by 38
Connectivity Between Brain Networks Dynamically Reflects Cognitive Status of Parkinson’s Disease: A Longitudinal Study
Klobušiaková, P., Mareček, R., Fousek, J., Výtvarová, E., & Rektorová, I. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-180834 · Cited by 40
“Effect size (p̂) was calculated according to Grissom and Kim (2012) [49], for details see the Supplementary Material.”
Method
The effectiveness of somatosensory retraining for improving sensory function in the arm following stroke: a systematic review
Turville, M. L., Cahill, L. S., Matyas, T. A., Blennerhassett, J. M., & Carey, L. M. (2019) · Clinical Rehabilitation · doi:10.1177/0269215519829795 · Cited by 39
Stochastic simulation of time-biased gain
Smucker, M. D., & Clarke, C. L. A. (2012) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2396761.2398568 · Cited by 37
A Single Counterexample Leads to Moral Belief Revision
Horne, Z., Powell, D., & Hummel, J. E. (2015) · Cognitive Science · doi:10.1111/cogs.12223 · Cited by 37
Technical Adequacy of the Social, Academic, and Emotional Behavior Risk Screener in an Elementary Sample
Kilgus, S. P., Sims, W. A., von der Embse, N. P., & Taylor, C. N. (2016) · Assessment for Effective Intervention · doi:10.1177/1534508415623269 · Cited by 37
“Each test yields a Mann– Whitney U statistic and corresponding p value, as well as an effect size statistic (Grissom & Kim, 2012).”
BackgroundMethodInfluential
Shame and the psychosis continuum: A systematic review of the literature
Carden, L. J., Saini, P., Seddon, C., Watkins, M., & Taylor, P. J. (2018) · Psychology and Psychotherapy Theory Research and Practice · doi:10.1111/papt.12204 · Cited by 45

Authors: Grissom, R. J., & Kim, J. J.
Affiliations: San Francisco State University (US)
ORCID: Kim, John J.
Venue: Routledge eBooks
Publisher: Routledge
Published: 2012-04-23
DOI: 10.4324/9780203803233
OpenAlex: W2892211387
Cited by: 470
References: 0
Citations by year: 2026: 41 · 2025: 27 · 2024: 27 · 2023: 31 · 2022: 37 · 2021: 23 · 2020: 34 · 2019: 40 · 2018: 44 · 2017: 24 · 2016: 47 · 2015: 31 · 2014: 33 · 2013: 23 · 2012: 8
FWCI: 12.17
Type: book
Language: en
Open access: closed
Locations: Routledge eBooks (publishedVersion)
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
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: effect size, confidence intervals, standardized mean difference, correlation measures, associative strength, covariance analysis, multiple linear regression, multivariate analysis of variance, repeated measures, robust estimators, statistical assumptions

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