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Comparing effect sizes in follow-up studies: ROC Area, Cohen's d, and r.
Abstract
In order to facilitate comparisons across follow-up studies that have used different measures of effect size, we provide a table of effect size equivalencies for the three most common measures: ROC area (AUC), Cohen's d, and r. We outline why AUC is the preferred measure of predictive or diagnostic accuracy in forensic psychology or psychiatry, and we urge researchers and practitioners to use numbers rather than verbal labels to characterize effect sizes.
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“The magnitude of the effects of these risk domains ranged from small (i.e., r= 0.099 for “low IQ/learning difficulties”) to large (i.e., r= 0.553 for “having a negative school attitude”) based on the criteria of Rice and Harris (2005) for interpreting effect sizes.”
From Risk Factors for School Absenteeism and Dropout: A Meta-Analytic Review (2019) · cites this paper as Rice and Harris (2005)
In the citing paper
“The AUC of 0.62 is also a moderate effect size [14], but is less than that for deadly violence (but this difference was not statistically significant).”
From The Domestic Abuse, Stalking and Harassment and Honour-Based Violence (DASH) Risk Assessment Instrument in Predicting Deadly or Persistent Domestic Abuse (2025) · cites this paper as [14]
In the citing paper
“The AUC of 0.67 for deadly violence is regarded as a “moderate” effect size [14].”
From The Domestic Abuse, Stalking and Harassment and Honour-Based Violence (DASH) Risk Assessment Instrument in Predicting Deadly or Persistent Domestic Abuse (2025) · cites this paper as [14]
In the citing paper
“AUC values of 0.56, 0.64, and 0.71 indicate small, medium, and large effects (Rice & Harris, 2005).”
From Strategies for monitoring mentoring relationship quality to predict early program dropout (2022) · cites this paper as Rice & Harris, 2005
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“AUC also has a plain language interpretation because it is conceptually and mathematically similar to the common language effect size or CL ( McGraw & Wong, 1992; see also Delaney & Vargha, 2002).”
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“71 as large effects (Rice and Harris, 2005).”
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“AUC values greater than 70% are considered good, whereas AUC values exceeding 90% are considered excellent (Rice & Harris, 2005).”
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“As a rough heuristic, an AUC of .560 corresponds to a small effect size, while .640 reflects a moderate effect, and .710 reflects a large effect size, as these values roughly correspond to Cohen’s ds of .20, .50, and .80 (see Rice & Harris, 2005).”
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“Although there is considerable variability in what constitutes a small, moderate, and large value for AUC (Singh et al., 2013), there is general agreement that this effect size represents good discrimination (Rice & Harris, 2005).”
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“However, Rice and Harris (2005) raised concerns about the thumb rule of 0.”
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“Rice and Harris (2005) calculated effect size equivalents for AUC scores using Cohen’s (1992) d statistic – a measure of the size of the effect in outcomes achieved when comparing one intervention with another or with treatment as usual.”
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“Values of 0.50 indicate chance level predictive accuracy, whereas values of 0.56, 0.64, and 0.71 represent small, medium, and large effect sizes, respectively (Rice & Harris, 2005).”
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“For the prediction of sexual recidivism, area under the curve (AUC) was used as an effect size statistic (see Swets, Dawes, & Monahan, 2000) in which AUCs of .56, .64, and .71 were considered small, medium, and large effects, respectively (Rice & Harris, 2005).”
MethodA Critique of the Historical Clinical Risk–20, Version 3, Risk Assessment Instrument
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“Table 2 shows the classification of effect size (Rice & Harris, 2005) and compares AUC and Cohen’s d (1969).”
BackgroundThe MATS-1 Risk Assessment Scale
Helmus, L., & Thornton, D. (2016) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063214529801 · Cited by 14
“…from Receiver Operating Characteristic Curves [ROC] analyses) are still the most commonly used and recommended statistic for risk assessment scales (Rice & Harris, 2005; Swets, Dawes, & Monahan, 2000), as well as Cox or logistic regression coefficients, which have become more commonly used and…”
BackgroundMethodvan der Put, C. E., Hermanns, J., Gelderen, L. V. R.-V., & Sondeijker, F. (2016) · BMC Psychiatry · doi:10.1186/s12888-016-0715-y · Cited by 14
“Rice ME, Harris GT. Comparing effect sizes in follow-up studies: ROC Area, Cohen's d, and r. Law Hum Behav.”
MethodInfluentialCiardha, C. Ó., Alleyne, E., Tyler, N., Barnoux, M., Mozova, K., & Gannon, T. A. (2015) · Psychology Crime and Law · doi:10.1080/1068316x.2015.1008478 · Cited by 14
“This performed at a level greater than chance; area under the curve (AUC) = .70, p < .001, 95% CI [.64, .77] corresponding to a Cohen’s d effect size of approximately 1.05 (Rice & Harris, 2005).”
BackgroundInfluentialWheeler, J. R., Clare, I. C. H., & Holland, A. J. (2013) · Psychology Crime and Law · doi:10.1080/1068316x.2013.854789 · Cited by 19
“The AUC for the accumulated proximal negative social and environmental risk scores was 0.817 (SE = 0.06), which was significantly above chance (p < 0.001), and according to convention, a large (>0.71, Rice & Harris, 2005) effect size.”
InfluentialLangton, C. M., Hogue, T. E., Daffern, M., Mannion, A., & Howells, K. (2009) · Psychology Crime and Law · doi:10.1080/10683160802516224 · Cited by 14
Courtney, D., Iseyas, N., Monga, S., Butcher, N. J., Krause, K. R., Besa, R., & Szatmári, P. (2023) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2023.10.013 · Cited by 17
Mayes, T. L., Carmody, T. J., Rush, A. J., Nandy, K., Emslie, G. J., Kennard, B. D., Forbes, K., Jha, M. K., Hughes, J. L., Heerschap, J. K., et al. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115306 · Cited by 19
“Thus, AUCs of 0.56, 0.64, and 0.71 are considered small, medium, and large, respectively (Rice and Harris, 2005).”
InfluentialPredicting and Optimising the Strength of Cemented Paste Fills Through Bayesian Network Model
Mishra, K., Paul, P. S., Ghosh, C. N., Singh, P., Behera, S., & Mandal, P. K. (2022) · Mining Metallurgy & Exploration · doi:10.1007/s42461-022-00650-9 · Cited by 13
Eke, A. W., & Seto, M. (2022) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/10790632221108951 · Cited by 13
“As per calculations by Rice and Harris (2005) and the AUC conversion table by Salgado (2018), AUC values of 0.56, 0.64, and 0.71 were considered small, moderate and large effect sizes as they roughly translate to Cohen’s d values of 0.20, 0.50, and 0.80.”
MethodInfluentialPredictors of perceived success in quitting smoking by vaping: A machine learning approach
Fu, R., Schwartz, R., Mitsakakis, N., Diemert, L. M., O'Connor, S. C., & Cohen, J. E. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262407 · Cited by 13
de Vogel, V., Stam, J., Bouman, Y., Horst, P. T., & Lancel, M. (2021) · Journal of Forensic Psychology Research and Practice · doi:10.1080/24732850.2021.1945833 · Cited by 13
“Rice and Harris (2005) have provided guidelines for interpreting AUC values: AUC values between .56 and .64 can be compared to Cohen’s d of .20 and are interpreted as low effect; AUC values between .64 and .71 to Cohen’s d of .50, medium effect; and AUC values of .71 and above to Cohen’s d of .80,…”
BackgroundAn Item Response Theory-Based Scoring of the South Oaks Gambling Screen–Revised Adolescents
Anselmi, P., Colledani, D., Andreotti, A., Robusto, E., Fabbris, L., Vian, P., Genetti, B., Mortali, C., Minutillo, A., Mastrobattista, L., et al. (2021) · Assessment (Odessa, Fla.) · doi:10.1177/10731911211017657 · Cited by 13
“In applied psychology, values about 0.70 are considered satisfactory (Rice & Harris, 2005).”
BackgroundInfluentialSimpson, A. D. J., Joshi, C., & Polaschek, D. (2021) · doi:10.1177/0093854821997525 · Cited by 13
“…aThe number of aggressors in the subsample and the percentage of aggressors with a recurrence in the subsample. bInterpretive criteria for AUCs from Rice and Harris (2005): .56–.63 = small, .64–.70 = moderate, .71–1.0 = large. moderate-risk category of the SAFVR should be “screened out” with the…”
BackgroundMethodInfluentialJuvenile Psychopathy and Community Treatment Response in Youth Adjudicated for Sexual Offenses
Rojas, E. Y., & Olver, M. (2021) · International journal of offender therapy and comparative criminology · doi:10.1177/0306624x21994066 · Cited by 13
“With an AUC of .50 representing chance level predictive accuracy, values of .56, .64, and .71 correspond to small, medium, and large effect sizes, respectively (Rice & Harris, 2005).”
MethodInvestigating the predictive validity of Static-99/99R scores in a sample of older sexual offenders
Raymond, B., Mcewan, T., Davis, M., Reeves, S. G., & Ogloff, J. (2020) · Psychiatry, Psychology and Law · doi:10.1080/13218719.2020.1767714 · Cited by 13
“Some authors argue a preference to not label AUC effects (Rice & Harris, 2005; Mossman, 2013) as it can be misleading due to differing definitions of what is considered small, moderate or large effects.”
BackgroundAcute and Chronic Effects of Betel Quid Chewing on Brain Functional Connectivity
Sariah, A., Guo, S., Zuo, J., Pu, W., Liu, H., Rolls, E. T., Xue, Z., Liu, Z., & Huang, X. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00198 · Cited by 13
“7 as having strong effects in test performance (59).”
BackgroundHaarsma, G., Davenport, S., White, D. C., Ormachea, P. A., Sheena, E., & Eagleman, D. M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02926 · Cited by 23
“We measure the NCRA via the ROC AUC, as this is the most widely used method in measuring predictive validity in risk assessments (Rice and Harris, 2005; Singh et al., 2013).”
MethodPrediction of Youth and Adult Recidivism Among Spanish Juveniles Involved in Serious Offenses
Cuervo, K., Villanueva, L., & Basto-Pereira, M. (2020) · doi:10.1177/0093854819897282 · Cited by 13
Roni, S. M., & Merga, M. K. (2019) · Australian Journal of Education · doi:10.1177/0004944119880621 · Cited by 23
Baglivio, M. T., & Wolff, K. T. (2018) · Youth Violence and Juvenile Justice · doi:10.1177/1541204018804870 · Cited by 16
McGrath, A., Thompson, A., & Goodman-Delahunty, J. (2018) · Criminal Justice and Behavior · doi:10.1177/0093854818762468 · Cited by 13
“The point biserial correlation coefficient observed for the full sample was .31 and that represents a medium to large effect size for a base rate of 37.5% (Rice & Harris, 2005).”
MethodInfluentialCuervo, K., & Villanueva, L. (2017) · International journal of offender therapy and comparative criminology · doi:10.1177/0306624x17741250 · Cited by 13
“The area under the curve (AUC) statistic was selected due to its accuracy for predicting recidivism (Rice & Harris, 2005; Swets, Dawes, & Monahan, 2000).”
MethodSome notes on the validation of VRS-SO static scores
Olver, M., Klepfisz, G., Stockdale, K. C., Kingston, D. A., Nicholaichuk, T., & Wong, S. C. P. (2016) · doi:10.1080/13552600.2015.1116625 · Cited by 13
“We interpreted AUC values in terms of effect size magnitudes employing the Rice and Harris (2005) guidelines of small (.56–.63), medium (.64–.70), and large (.71+).”
MethodInfluentialShort-Term General Recidivism Risk of Juvenile Sex Offenders
van der Put, C. E., van Vugt, E., Stams, G., Deković, M., & van der Laan, P. H. (2013) · International journal of offender therapy and comparative criminology · doi:10.1177/0306624x12457775 · Cited by 13
Looman, J., Morphett, N. A. C., & Abracen, J. (2013) · International journal of offender therapy and comparative criminology · doi:10.1177/0306624x12444839 · Cited by 13
“The r value for the proportional index corresponds with a d value of approximately 0.45 (Rice & Harris, 2005), which exceeds that found for phallometric assessment of sexual interest in children in the Mann et al. (2010) meta-analysis (d = 0.32, 95% confidence interval [CI] = [0.16, 0.47]).”
MethodInfluentialQuinn, R. E., Miles, H., & Kinane, C. (2013) · doi:10.1080/14999013.2013.832714 · Cited by 13
“The Area Under the Curve (AUC) coefficient represents the effect size, where AUCs between 0.56–0.63 are considered small effects (0.50 is chance), AUCs between 0.64–0.70 are medium effects and AUCs above 0.71 are described as large effects (Rice & Harris, 2005).”
BackgroundInfluentialEducating Engineering Undergraduates: Effects of Scaffolding in a Problem-Based Learning Environment
Mayer, R. R., Moeller, B. F., Kaliwata, V., Zweber, B., Stone, R., & Frank, M. (2012) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181312561510 · Cited by 13
Predicting sexual re-offending in a UK sample of adolescents with intellectual disabilities
Griffin, H., & Vettor, S. (2012) · doi:10.1080/13552600.2011.617013 · Cited by 13
“Rice and Harris (2005) studied the relationship and equivalencies between ROC area (AUC) and Cohen’s d.”
BackgroundMethodRettenberger, M., Mönichweger, M., Buchelle, E., Schilling, F., & Eher, R. (2010) · doi:10.1515/mks-2010-930503 · Cited by 13
“…zurück (z.B. Egan 1975) und weisen gegenüber herkömmlichen korrelativen Verfahren eine Reihe methodischer Vorteile auf (vgl. z.B. Seto 2005; Rice & Harris 1995; 2005; Mossman 1994; Dahle 2007), so dass bei der Überprüfung der diagnostischen und/oder prognostischen Qualität von…”
BackgroundSischka, P., Schmidt, A. F., & Steffgen, G. (2020) · European Journal of Psychological Assessment · doi:10.1027/1015-5759/a000483 · Cited by 13
Ammari, T., Ahn, E., Lakhankar, A., & Lee, J. Y. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3710985 · Cited by 12
“…transitioned from trauma, we found that some forums that we considered early on were more emotional as they cater for survivors who might be responding to more recent trauma (e.g., ‘r/sexualassault’) where the focus is on accessing more immediate support as opposed to reconstructing one’s…”
Victims of Child Abuse Dropping Out of Trauma-Focused Treatment: A Meta-Analysis of Risk Factors
van der Hoeven, M. L., Assink, M., Stams, G. J. J. M., Daams, J. G., Lindauer, R., & Hein, I. M. (2022) · Journal of Child & Adolescent Trauma · doi:10.1007/s40653-022-00500-2 · Cited by 14
“We interpreted effect sizes as small (r > 0.100), medium (r > 0.243), and large (r > 0.371) (Rice & Harris, 2005).”
MethodInfluentialA Look at the Difficulty and Predictive Validity of LS/CMI Items With Rasch Modeling
Giguère, G., Brouillette-Alarie, S., & Bourassa, C. (2022) · Criminal Justice and Behavior · doi:10.1177/00938548221131956 · Cited by 12
Metadata
- Authors
- Rice, M. E., & Harris, G. T.
- Affiliations
- Waypoint Centre for Mental Health Care (CA)
- Venue
- Law and Human Behavior
- Published
- 2005-10
- Volume
- 29
- Issue
- 5
- Pages
- 615-620
- ISSN
- 0147-7307 (ISSN-L)
- 1573-661X
- OpenAlex
- W2060774914
- Cited by
- 1,608
- References
- 0
- Citations by year
- 2026: 60 · 2025: 84 · 2024: 90 · 2023: 121 · 2022: 151 · 2021: 150 · 2020: 174 · 2019: 137 · 2018: 112 · 2017: 80 · 2016: 88 · 2015: 65 · 2014: 64 · 2013: 58 · 2012: 51
- FWCI
- 11.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Law and Human Behavior (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 › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- effect size, Cohen's d, diagnostic accuracy, prediction accuracy, forensic psychology, follow-up study
- MeSH terms
- Forecasting, Humans, ROC Curve, Risk Assessment
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