The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
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
Citations
Cites
Meta-Analytic Procedures for Social Research
Rosenthal, R. (1991) · doi:10.4135/9781412984997 · Cited by 4,635
Interpreting the magnitudes of correlation coefficients.
Hemphill, J. F. (2003) · American Psychologist · doi:10.1037/0003-066x.58.1.78 · Cited by 1,237
A common language effect size statistic
McGraw, K. O., & Wong, S. P. (1992) · Psychological Bulletin · doi:10.1037/0033-2909.111.2.361 · Cited by 934 · cited 1×
“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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- Berlin, F. S., Galbreath, N. W., Geary, B., & McGlone, G. (2003). The use of actuarials at civil commitment hearings to predict the likelihood of future sexual violence. Sexual Abuse: A Journal of Research and Treatment, 15, 377–382. · DOI
- Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York: Academic Press.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
- Cohen, J. (1992). A power primer. Psychological Bulletin, 122, 155–159. · DOI · Paper page
- Delaney, H. D., & Vargha, A. (2002). Comparing several robust tests of stochastic equality with ordinally scaled variables and small to moderate sized samples. Psychological Methods, 7, 485–503. · DOI
- Harris, G. T., & Rice, M. E. (2003). Actuarial assessment of risk among sex offenders. In R. A. Prentky, E. S. Janus, & M. C. Seto (Eds.), Understanding and managing sexually coercive behavior, Vol. 989 (pp. 198–210). New York: Annals of the New York Academy of Sciences. · DOI
- Mossman, D. (1994). Assessing predictions of violence being accurate about accuracy. Journal of Consulting and Clinical Psychology, 62, 783–792. · DOI
- Pearson, E. S., & Hartley, H. O. (Eds.). (1954). Biometrika tables for statisticians, Vol. 1 (1st ed.). Cambridge: Cambridge University Press.
- Rice, M. E., & Harris, G. T. (1995). Violent recidivism: Assessing predictive validity. Journal of Consulting and Clinical Psychology, 63, 737–748. · DOI
- Rosenthal, R. (1990). How are we doing in soft psychology? American Psychologist, 45, 775–777. · DOI
- Rosenthal, R., & Rubin, D. B. (1982). A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology, 74, 166–169. · DOI
- Swets, J. A. (1986). Indices of discrimination or diagnostic accuracy: Their ROCs and implied models. Psychological Bulletin, 99, 100–117. · DOI
- Swets, J. A., Dawes, R. M., & Monahan, J. (2000). Psychological science can improve diagnostic decisions. Psychological Science in the Public Interest: A Journal of the American Psychological Society, 1, 1–26. · DOI
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Meier, M. H., Hall, W., Caspi, A., Belsky, D. W., Cerdá, M., Harrington, H., Houts, R., Poulton, R., & Moffitt, T. E. (2015) · Psychological Medicine · doi:10.1017/s0033291715002482 · Cited by 81
“AUC values of 0.54, 0.64, and 0.71 correspond to Cohen’s d values of 0.20, 0.50, and 0.80, and reflect small, medium, and large effects, respectively (Rice & Harris, 2005).”
BackgroundInfluentialKnox, M. J., Willard-Grace, R., Huang, B., & Grumbach, K. (2018) · Journal of general internal medicine · doi:10.1007/s11606-018-4507-6 · Cited by 79
Howard, P., & Dixon, L. (2013) · Law and Human Behavior · doi:10.1037/lhb0000012 · Cited by 79
“Rice and Harris (2005) suggested that an AUC of 0.639 represents a medium effect size and an AUC of 0.714 represents a large effect size.”
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Warmelink, L., Vrij, A., Mann, S. A., Leal, S., Forrester, D., & Fisher, R. P. (2010) · Law and Human Behavior · doi:10.1007/s10979-010-9251-3 · Cited by 77
“The mean areas under the curve (AUCs) were .71 for Phase 2 and .74 for Phase 3, the equivalent of Cohen’s d’s of d = .80 and d = .83 respectively ( Rice & Harris, 2005 ).”
MethodAn Examination of the Predictive Validity of the Risk Matrix 2000 in England and Wales
Barnett, G., Wakeling, H., & Howard, P. (2010) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063210384274 · Cited by 79
“Finally, Hanson and MortonBourgon’s (2009) meta-analysis found the RM2000/s and v scales to have good predictive accuracy for sexual reconviction (d = 0.67, which equates to an AUC of .68; Rice & Harris, 2005) and violent reconviction (d = 0.62, AUC = .67), respectively.”
BackgroundMethodResultInfluentialBengtson, S., & Långström, N. (2007) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/107906320701900205 · Cited by 79
Predictive Validity of Pretrial Risk Assessments: A Systematic Review of the Literature
Desmarais, S. L., Zottola, S. A., Duhart Clarke, S. E., & Lowder, E. M. (2021) · Criminal Justice and Behavior · doi:10.1177/0093854820932959 · Cited by 79
Morrissey, C., Hogue, T. E., Mooney, P., Allen, C. L., Johnston, S., Hollin, C., Lindsay, W., & Taylor, J. L. (2007) · doi:10.1080/08990220601116345 · Cited by 78
“In line with recommendations by Rice and Harris (2005) regarding measures of predictive accuracy, receiver operating characteristic (ROC) analyses were also conducted.”
MethodPérez-Cruzado, D., Merchán-Baeza, J., Gónzalez-Sánchez, M., & Cuesta-Vargas, A. (2017) · Australian Occupational Therapy Journal · doi:10.1111/1440-1630.12342 · Cited by 77
O'Shea, L., Mitchell, A., Picchioni, M., & Dickens, G. (2013) · Aggression and Violent Behavior · doi:10.1016/j.avb.2012.11.016 · Cited by 77
An Examination of Two Sexual Recidivism Risk Measures in Adolescent Offenders
Rajlic, G., & Gretton, H. (2010) · Criminal Justice and Behavior · doi:10.1177/0093854810376354 · Cited by 77
“Both J-SOAP-II total score and ERASOR total score predicted sexual recidivism significantly better than chance (J-SOAP-II, AUC = .69, p = .003; ERASOR, AUC = .71, p < .001; equivalent to medium effect sizes; Rice & Harris, 2005).”
BackgroundBoccaccini, M., Murrie, D., Caperton, J. D., & Hawes, S. (2009) · doi:10.1037/a0017232 · Cited by 77
Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment.
Eher, R., Olver, M., Heurix, I., Schilling, F., & Rettenberger, M. (2015) · Law and Human Behavior · doi:10.1037/lhb0000144 · Cited by 76
Wakeling, H., Howard, P., & Barnett, G. (2011) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063210375974 · Cited by 76
Siehl, S., Robjant, K., & Crombach, A. (2020) · Psychotherapy Research · doi:10.1080/10503307.2020.1847345 · Cited by 100
“On the descriptive level, the difference between these effect sizes of short- and long-term efficacy within RCT studies could tentatively be considered a small effect in favor of the long-term outcome (SMD RCT studies<6months = 1.06 < SMD RCT studies≥6months = 1.26; Rice & Harris, 2005).”
BackgroundInfluentialGender, risk assessment, and sanctioning: The cost of treating women like men.
Skeem, J. L., Monahan, J. T., & Lowenkamp, C. T. (2016) · Law and Human Behavior · doi:10.1037/lhb0000206 · Cited by 103
Actuarial prediction of violent recidivism in mentally disordered offenders
Snowden, R., Gray, N., Taylor, J., & Macculloch, M. (2007) · Psychological Medicine · doi:10.1017/s0033291707000876 · Cited by 75
Risk, Race, & Recidivism: Predictive Bias and Disparate ImpactPreprint
Skeem, J., & Lowenkamp, C. T. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2687339 · Cited by 73
Adults' ability to detect children's lying.
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Smolen, J., Gladman, D., McNeil, H., Mease, P., Sieper, J., Hojnik, M., Nurwakagari, P., & Weinman, J. (2019) · RMD Open · doi:10.1136/rmdopen-2017-000585 · Cited by 72
“70 are considered strong effects.(26) The predictive accuracy of our AS adherence prediction model exceeded an AUROC of 0.”
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Pusch, N., & Holtfreter, K. (2018) · doi:10.1177/0093854817721720 · Cited by 71
“To solve this problem, AUC scores were converted into pointbiserial correlation scores (r) using the table provided by Rice and Harris (2005).”
BackgroundMethodInfluentialMessing, J., Campbell, J., & Snider, C. (2017) · Journal of Advanced Nursing · doi:10.1111/jan.13459 · Cited by 71
“Sample size estimates were calculated by iterative approximation (Hanley & McNeil, 1982) and indicate that 619 participants provides sufficient power to detect an AUC of .60 (standard error = 0.02), which corresponds to a small effect (Rice & Harris, 2005).”
BackgroundMethodInfluentialOlver, M., Christofferson, S. B. B., Grace, R., & Wong, S. C. P. (2014) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063213502679 · Cited by 71
“Using the guidelines provided in Rice and Harris (2005), we interpret rpb, d, and AUC values in terms of effect size magnitudes using the language of small/ low (AUC = .556-.637, Cohen’s d = .20, rpb = .10), medium (AUC = .639-.712. d = .50, rpb = .243) and large/high (AUC = .714 and up, d = .80,…”
MethodComparing indicators of sexual sadism as predictors of recidivism among adult male sexual offenders.
Kingston, D. A., Seto, M., Firestone, P., & Bradford, J. M. W. (2010) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0019734 · Cited by 71
“For descriptive purposes, AUC values of .56, .64 and .71 can be described as small, medium, and large, respectively (Rice & Harris, 2005).”
Wakeling, H., Beech, A., & Freemantle, N. (2013) · Psychology Crime and Law · doi:10.1080/1068316x.2011.626413 · Cited by 70
“We follow the interpretation suggested by Rice and Harris (2005), and Douglas, Epstein, and Poythress (2008), where comparisons to Cohen’s d suggest that an AUC value of 0.71 represents a large effect size and an AUC value of 0.64 represents a moderate effect size.”
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Emotional congruence with children and sexual offending against children: A meta-analytic review.
McPhail, I. V., Hermann, C. A., & Nunes, K. L. (2013) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0033248 · Cited by 70
Hypersexuality and Recidivism among Sexual Offenders
Kingston, D. A., & Bradford, J. M. (2013) · Sexual Addiction & Compulsivity · doi:10.1080/10720162.2013.768131 · Cited by 69
“For descriptive purposes, AUC values of .56, .64 and .71 can be described as small, medium, and large, respectively (Rice & Harris, 2005).”
Messing, J. T., Campbell, J. C., Wilson, J. S., Brown, S., & Patchell, B. (2015) · Journal of Interpersonal Violence · doi:10.1177/0886260515585540 · Cited by 87
“Finally, the Receiver Operating Characteristic Area Under the Curve (AUC) is the suggested method of examining predictive validity and takes into account both sensitivity and specificity in a single analysis (Rice & Harris, 2005).”
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“Among Aboriginal youths, the three-factor and four-factor models had significant and moderate to high predictive accuracy (e.g., Rice & Harris, 2005) for combined youth–adult and youth recidivism outcomes.”
InfluentialElek, E., Wagstaff, D., & Hecht, M. (2010) · Journal of Drug Education · doi:10.2190/de.40.1.e · Cited by 69
“Indeed, effect sizes were estimated with an appropriate expression of Cohen’s d (Cohen, 1989; Rice & Harris, 2005) and the requisite pooled standard deviation was estimated using a complex sample survey routine.”
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“For practical situations, an AUC of over 70% is desirable [59].”
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Pallavicini, F., & Pepe, A. (2019) · Annual Symposium on Computer-Human Interaction in Play · doi:10.1145/3341215.3355736 · Cited by 77
Risks, strengths, gender, and recidivism among justice-involved youth: A meta-analysis.
Scott, T., & Brown, S. L. (2018) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000343 · Cited by 96
de Vogel, V., & Lancel, M. (2016) · doi:10.1080/14999013.2016.1138173 · Cited by 68
“Receiver operating characteristics (ROC; Mossman, 1994; Rice & Harris, 2005) analyses were carried out to assess predictive validity of the PCL-R facets and total scores for incidents during treatment.”
MethodReview of Risk Assessment Instruments for Juvenile Sex Offenders
Hempel, I., Buck, N., Cima, M., & van Marle, H. (2013) · International journal of offender therapy and comparative criminology · doi:10.1177/0306624x11428315 · Cited by 68
“Two effect sizes for risk assessment studies are suggested in the literature: point biserial correlation (r) and area under the curve (AUC) statistic from receiver operator characteristic curve analysis (Rice & Harris, 2005).”
BackgroundCategorical meta-analysis of Osteopontin as a clinical cancer marker.
Weber, G., Lett, G. S., & Haubein, N. C. (2011) · Oncology Report · doi:10.3892/or.2010.1106 · Cited by 68
“will also have a higher rank for the clinical variable in question (9).”
Generalization and Personalization of Mobile Sensing-Based Mood Inference Models
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“In addition, since p-values are limited in determining statistical significance [54], we also report Cohen’s-d [86] (all features have 95% confidence interval not crossing zero [52]) for positive, neutral, and negative classes for each country.”
BackgroundAssessing risk for aggression in forensic psychiatric inpatients: An examination of five measures.
Hogan, N. R., & Olver, M. (2016) · Law and Human Behavior · doi:10.1037/lhb0000179 · Cited by 67
Polaschek, D. (2011) · Journal of Interpersonal Violence · doi:10.1177/0886260510365854 · Cited by 67
“Rice and Harris (2005) noted that 25% is a more typical base rate in studies of violent recidivism.”
BackgroundMorrissey, C., Mooney, P., Hogue, T. E., Lindsay, W., & Taylor, J. L. (2007) · Journal of Intellectual & Developmental Disability · doi:10.1080/13668250701383116 · Cited by 67
“In line with the recommendations of Rice and Harris (2005) in relation to predictive studies, ROC analyses were also conducted as an alternative measure of predictive validity.”
MethodSadism and Violent Reoffending in Sexual Offenders
Eher, R., Schilling, F., Hansmann, B., Pumberger, T., Nitschke, J., Habermeyer, E., & Mokros, A. (2015) · Sexual Abuse · doi:10.1177/1079063214566715 · Cited by 78
“According to Rice and Harris (2005), AUC values equal to or above .56, .64, and .71 would represent small, medium, or large effect sizes, respectively.”
BackgroundA multisite examination of sexual violence risk and therapeutic change.
Olver, M., Nicholaichuk, T., Kingston, D. A., & Wong, S. C. P. (2014) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0035340 · Cited by 66
Bengtson, S. (2008) · Psychology Crime and Law · doi:10.1080/10683160701483104 · Cited by 66
“Tape’s (2006) guidelines are far more strict than those recommended by Rice and Harris (2005) but appear similar to those recommended by Sjöstedt and Grann (2002).”
MethodThe field validity of Static-99/R sex offender risk assessment tool in California.
Hanson, R. K., Lunetta, A., Phenix, A., Neeley, J., & Epperson, D. L. (2014) · Journal of Threat Assessment and Management · doi:10.1037/tam0000014 · Cited by 79
Predicting the sensitivity of the Reaction Time-based Concealed Information Test
Noordraven, E., & Verschuere, B. (2013) · Applied Cognitive Psychology · doi:10.1002/acp.2910 · Cited by 65
A Validation Study of the Child Pornography Offender Risk Tool (CPORT)
Eke, A. W., Helmus, L., & Seto, M. C. (2019) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063218762434 · Cited by 64
Olver, M., Marshall, L., Marshall, W. L., & Nicholaichuk, T. (2018) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063218807486 · Cited by 64
“Predictive accuracy was examined through AUC analyses in which values of .56, .64, and .71 correspond to low, medium, and large effect sizes, respectively (Rice & Harris, 2005).”
MethodRisk Assessment Among Incarcerated Male Domestic Violence Offenders
Hilton, N. Z., Harris, G. T., Popham, S. M., & Lang, C. (2010) · Criminal Justice and Behavior · doi:10.1177/0093854810368937 · Cited by 75
“A version of this instrument (LSI–Ontario Revision [LSI-OR]; Andrews, Bonta, & Wormith, 1995) predicted recidivism among 698 offenders with an ROC area of .73 for general criminal recidivism and .68 for violent recidivism (Girard & Wormith, 2004).”
MethodInfluentialSelf-citationDigital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism
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“While the predictive power of emotional expression in some of the videos varied, all but one represent a medium effect, equivalent to Cohen’s d = 0.5 or greater [Rice & Harris, 2005].”
InfluentialNon-Specialization of Criminal Careers Among Intimate Partner Violence Offenders
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Prospective Validity of the Estimate of Risk of Adolescent Sexual Offense Recidivism (ERASOR)
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“An effect size of this magnitude corresponds to an area under the receiver operating characteristic curve (AUC) of approximately 0.68 (Rice & Harris, 2005).”
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Miché, M., Studerus, E., Meyer, A. H., Gloster, A. T., Beesdo‐Baum, K., Wïttchen, H., & Lieb, R. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.11.093 · Cited by 69
Olver, M., Mundt, J., Thornton, D., Christofferson, S. B. B., Kingston, D. A., Sowden, J. N., Nicholaichuk, T., Gordon, A., & Wong, S. C. P. (2018) · Psychological Assessment · doi:10.1037/pas0000538 · Cited by 62
The federal Post Conviction Risk Assessment (PCRA): A construction and validation study.
Lowenkamp, C. T., Johnson, J. L., Holsinger, A. M., VanBenschoten, S. W., & Robinson, C. R. (2012) · Psychological Services · doi:10.1037/a0030343 · Cited by 53
Bowen, E. (2011) · Aggression and Violent Behavior · doi:10.1016/j.avb.2011.02.007 · Cited by 62
Psychopathy and Treatment Outcome: Results From a Sexual Violence Reduction Program
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Are risk assessments racially biased?: Field study of the SAVRY and YLS/CMI in probation.
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Walters, G. D., & Lowenkamp, C. T. (2015) · Psychological Assessment · doi:10.1037/pas0000210 · Cited by 66
Subgroup differences and implications for contemporary risk-need assessment with juvenile offenders.
Thompson, A. P., & McGrath, A. (2011) · Law and Human Behavior · doi:10.1037/h0093930 · Cited by 60
Möhring, A., Rumpf, H., Hapke, U., Bischof, G., John, U., & Meyer, C. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2019.06.032 · Cited by 83
Hamilton, H., Boos, A. K., & Mathalon, D. H. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.04.002 · Cited by 68
Amminger, G. P., Nelson, B., Markulev, C., Yuen, H. P., Schäfer, M. R., Berger, M., Mossaheb, N., Schlögelhofer, M., Smesny, S., Hickie, I. B., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.08.030 · Cited by 67
Douglas, K. (2014) · Behavioral sciences & the law · doi:10.1002/bsl.2134 · Cited by 58
Edens, J. F. (2009) · Psychological Assessment · doi:10.1037/a0014856 · Cited by 56
Is there an allegiance effect for assessment instruments? Actuarial risk assessment as an exemplar.
Blair, P. R., Marcus, D. K., & Boccaccini, M. T. (2008) · Clinical Psychology Science and Practice · doi:10.1111/j.1468-2850.2008.00147.x · Cited by 63
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“The effect size was measured using the nonparametric common language effect size (CL) (52, 53).”
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Risk and Protective Factors for Recidivism Among Juveniles Who Have Offended Sexually
Spice, A., Viljoen, J. L., Latzman, N., Scalora, M. J., & Ullman, D. (2013) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063212459086 · Cited by 56
Rettenberger, M., Haubner-Maclean, T., & Eher, R. (2013) · Criminal Justice and Behavior · doi:10.1177/0093854813492518 · Cited by 56
“Helmus, Thornton, et al. (2012) also included a nonrepresentative subsample of our study’s sample that yielded an average Static-99 score of 2.7 (the same mean value as in the present sample). Only seven studies showed lower average total scores and two studies had the same average Static-99 score. This indicates that…”
ResultInfluentialOlver, M., Neumann, C., Wong, S. C. P., & Hare, R. (2013) · Psychological Assessment · doi:10.1037/a0029840 · Cited by 56
Harris, G., Lalumière, M., Seto, M., Rice, M., & Chaplin, T. C. (2012) · Archives of Sexual Behavior · doi:10.1007/s10508-012-9940-8 · Cited by 56
“…procedure and stimulus set clearly discriminated between rapists and non-rapists:ROCareas = .83,SE = .09,p\.01, for the Rape Index, and .80, SE = .09, p\.01 for the Assault Index, or Cohen’s d statistics of 1.34 and 1.20, respectively, large effects by customary standards (Rice & Harris, 2005).”
InfluentialSelf-citationLong-Term Predictive Validity of the Risk Matrix 2000
Kingston, D. A., Yates, P., Firestone, P., Babchishin, K., & Bradford, J. M. W. (2008) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063208325206 · Cited by 56
“For descriptive purposes, minimum AUC values of .56, .64, and .71 are described as small, medium, and large, respectively (Rice & Harris, 2005).”
BackgroundMethodInfluentialThe impact of context metrics on just-in-time defect prediction
Kondo, M., Germán, D., Mizuno, O., & Choi, E.-H. (2019) · Empirical Software Engineering · doi:10.1007/s10664-019-09736-3 · Cited by 55
Brouillette-Alarie, S., Proulx, J., & Hanson, R. K. (2017) · Sexual abuse. A Journal of Research and Treatment · doi:10.1177/1079063217691965 · Cited by 55
Resilience and Other Possible Outcomes After Mild Traumatic Brain Injury: a Systematic Review
Sullivan, K. A., Kempe, C. B., Edmed, S. L., & Bonanno, G. A. (2016) · Neuropsychology Review · doi:10.1007/s11065-016-9317-1 · Cited by 65
Helmus, L., & Bourgon, G. (2011) · International Journal of Forensic Mental Health · doi:10.1080/14999013.2010.551709 · Cited by 55
“Predictive accuracy is represented by the Area Under the Receiver Operating Characteristic Curve (AUC from ROC analyses), which is one of the most commonly used and recommended effect size statistics for recidivism prediction ( Rice & Harris, 2005 ).”
BackgroundMethodInfluentialRisk factors for recidivism in offenders with intellectual disabilities
Fitzgerald, S., Gray, N., Taylor, J., & Snowden, R. (2011) · Psychology Crime and Law · doi:10.1080/10683160903392293 · Cited by 55
“…of previous offences, number of previous acquisitive offences, number of previous drug offences, number of previous bail offences were all of a medium effect size (Rice & Harris, 2005), as was a history of drug abuse (Cohen, 1992); a history of alcohol abuse was a small effect size (Cohen, 1992).”
BackgroundMethodInfluentialMaternal programming of sex-specific responses to predator odor stress in adult rats
St-Cyr, S., Abuaish, S., Sivanathan, S., & McGowan, P. O. (2017) · Hormones and Behavior · doi:10.1016/j.yhbeh.2017.06.005 · Cited by 55
Racine, A. M., Tommet, D., D’Aquila, M., Fong, T. G., Gou, Y., Tabloski, P. A., Metzger, E. D., Hshieh, T. T., Schmitt, E. M., Vasunilashorn, S. M., et al. (2020) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06238-7 · Cited by 64
Using algorithms to address trade‐offs inherent in predicting recidivism
Skeem, J. L., & Lowenkamp, C. T. (2020) · Behavioral Sciences & the Law · doi:10.1002/bsl.2465 · Cited by 89
Breast Lesion Classification in Ultrasound Images Using Deep Convolutional Neural Network
Zeimarani, B., Costa, M., Nurani, N. Z., Bianco, S. R., Pereira, W. C. D. A., & Costa, C. (2020) · IEEE Access · doi:10.1109/access.2020.3010863 · Cited by 54
“According to [11], in medical image analysis, a very high sensitivity value and an AUC more than 0.95 are sought after, considering the vast popularity and success of CNNs in detection and classification of objects.”
BackgroundInfluentialDynamic Risk Assessment of Sexual Offenders: Validity and Dimensional Structure of the Stable-2007
Etzler, S., Eher, R., & Rettenberger, M. (2020) · Assessment (Odessa, Fla.) · doi:10.1177/1073191118754705 · Cited by 53
“…to as the gold standard method to assess diagnostic and predictive accuracy (e.g., Helmus & Babchishin, 2017; Lobo, Jiménez-Valverde, & Real, 2008; Rice & Harris, 2005), its accuracy has to be interpreted cautiously especially in samples with relatively low base rates because of the risk of a…”
BackgroundMethodShamizadeh, T., Jahangiry, L., Sarbakhsh, P., & Ponnet, K. S. (2019) · Trials · doi:10.1186/s13063-019-3220-z · Cited by 69
“The study was sufficiently powered to detect small-to-medium effects, as operationalized by Cohen’s d [28].”
BackgroundPredictive analytics and child protection: constraints and opportunities.
Russell, J. (2015) · International Journal of Child Abuse & Neglect · doi:10.1016/j.chiabu.2015.05.022 · Cited by 53
The Predictive Accuracy of Risk Factors in the Sexual Violence Risk–20 (Svr-20)
Rettenberger, M., Boer, D., & Eher, R. (2011) · Criminal Justice and Behavior · doi:10.1177/0093854811416908 · Cited by 53
“Referring to Cohen (1992), Dahle, Schneider, and Ziethen (2007; also see Rice & Harris, 2005) defined the following criteria for classifying the predictive accuracy of risk assessment tools: AUC values of .72 or greater (r ≥ .37) are classified as good, AUC values between .64 and .71 (r ≥ .24) are…”
BackgroundMethodThe meaning of significant mean group differences for biomarker discovery
Loth, E., Ahmad, J., Chatham, C., López, B., Carter, B., Crawley, D., Oakley, B., Hayward, H., Cooke, J., San José Cáceres, A., et al. (2021) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009477 · Cited by 52
The Development of a Short Chinese Version of the State-Trait Anxiety Inventory
Du, Q., Liu, H.-W., Yang, C.-J., Chen, X.-Y., & Zhang, X.-Y. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.854547 · Cited by 52
Dai, Y. G., Burke, J. D., Naigles, L. R., Eigsti, I.-M., & Fein, D. A. (2018) · Research in Autism Spectrum Disorders · doi:10.1016/j.rasd.2018.08.001 · Cited by 52
“Independent t-tests were performed to analyze continuous variables and effect sizes were estimated using Cohen’s d, where 0.2 is considered a small effect, 0.5 denotes a medium effect, and 0.8 indicates a large effect (Cohen, 1988; Rice & Harris, 2005).”
MethodInfluentialPredicting Teen Dating Violence Perpetration
Cohen, J. R., Shorey, R., Menon, S. V., & Temple, J. R. (2018) · Pediatrics · doi:10.1542/peds.2017-2790 · Cited by 52
Procalcitonin for the early diagnosis of sepsis in burn patients: A retrospective study
Cabral, L., Afreixo, V. M. A., Santos, F., Almeida, L., & Paiva, J. A. (2017) · Burns · doi:10.1016/j.burns.2017.03.026 · Cited by 59
Seto, M., & Eke, A. W. (2017) · Law and Human Behavior · doi:10.1037/lhb0000240 · Cited by 52
Incorporating Strengths Into Quantitative Assessments of Criminal Risk for Adult Offenders
Jones, N. J., Brown, S. L., Robinson, D., & Frey, D. (2015) · Criminal Justice and Behavior · doi:10.1177/0093854814547041 · Cited by 52
“The corresponding effect size rubric typically invoked within the field of correctional psychology was proposed by Rice and Harris (2005).”
BackgroundMethodInfluentialRamírez‐Vélez, R., Carrillo, H. A., Correa‐Bautista, J. E., Schmidt‐RioValle, J., González‐Jiménez, E., Correa‐Rodríguez, M., González‐Ruíz, K., & García‐Hermoso, A. (2018) · Nutrients · doi:10.3390/nu10081027 · Cited by 51
“However, AUCs values of 0.55–0.62, 0.63–0.71, and >0.71 corresponded to an effect size (Cohen’s d) of small, medium, and large, respectively [36].”
BackgroundInfluentialAssessing risk of sexually abusive behavior among youth in a child welfare sample.
Prentky, R., Li, N.-C., Righthand, S., Schuler, A., Cavanaugh, D. J., & Lee, A. F. S. (2010) · Behavioral sciences & the law · doi:10.1002/bsl.920 · Cited by 51
Beidas, R. S., Maclean, J. C., Fishman, J., Dorsey, S., Schoenwald, S. K., Mandell, D. S., Shea, J. A., McLeod, B. D., French, M. T., Hogue, A., et al. (2016) · BMC Psychiatry · doi:10.1186/s12888-016-1034-z · Cited by 50
Evans, R., Thirlwall, K., Cooper, P., & Creswell, C. (2017) · Psychological Assessment · doi:10.1037/pas0000375 · Cited by 58
Peña, E. D., Bedore, L. M., Lugo-Neris, M. J., & Albudoor, N. (2020) · Language Assessment Quarterly · doi:10.1080/15434303.2020.1827258 · Cited by 50
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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