The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Intraclass correlations: Uses in assessing rater reliability.
Abstract
Reliability coefficients often take the form of intraclass correlation coefficients. In this article, guidelines are given for choosing among six different forms of the intraclass correlation for reliability studies in which n target are rated by k judges. Relevant to the choice of the coefficient are the appropriate statistical model for the reliability and the application to be made of the reliability results. Confidence intervals for each of the forms are reviewed.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As a result, the inter-rater agreement was quite high for categorical variables (mean Cohen's kappa = 0.73, SD = 0.13) and for continuous variables (mean intraclass correlation [26] = 0.80, SD = .14).”
From Social Relationships and Mortality Risk: A Meta-analytic Review (2010) · cites this paper as [26]
In the citing paper
“we used the methodology Shrout and Fleiss (1979) describe and computed the Shrout-Fleiss single ICC score agreement of .998, which is considered quite high (Koo and Li 2016).”
From Driving Brand Engagement Through Online Social Influencers: An Empirical Investigation of Sponsored Blogging Campaigns (2019) · cites this paper as Shrout and Fleiss (1979)
In the citing paper
“In contrast, Cohen's quadratically weighted kappa converges to two-factor intraclass correlation coefficients with random and fixed raters (i.e., the so-called ICC (2,1) and ICC(3,1) coefficients), where the items and raters are the two factors (Carrasco, 2010;Fleiss & Cohen, 1973;Janson & Olsson, 2001;Schuster, 2004;Schuster & Smith, 2005;Shrout & Fleiss, 1979;Warrens, 2014).”
From Quadratically Weighted Agreement Coefficients: Interpretations and Connections (2026) · cites this paper as Shrout & Fleiss, 1979
In the citing paper
“A sample of 11% of video data was double coded by the researcher and an experienced coder (the developer of CHIPPA). Inter‐rater reliability was based on intra‐class correlation (ICC) statistics from the mean rating for the two coders (k = 2) using a two‐way mixed effects consistency model (see Table 2 below) and resulted in good to excellent reliability across the CHIPPA subscales (Koo & Li, 2016”
From A plausible role of imagination in pretend play, counterfactual reasoning, and executive functions (2023) · cites this paper as Shrout & Fleiss, 1979
In the citing paper
“The results suggest that coders showed high agreement (intraclass correlation [2, 1] = 0.85; Shrout & Fleiss, 1979).”
From Respiratory and cognitive mediators of treatment change in panic disorder: Evidence for intervention specificity. (2010) · cites this paper as Shrout & Fleiss, 1979
In the citing paper
“Interrater reliability of the pre- and posttreatment assessments was excellent (intraclass correlations [2, 1] = 0.97 and 0.96, respectively; Shrout & Fleiss, 1979).”
From Respiratory and cognitive mediators of treatment change in panic disorder: Evidence for intervention specificity. (2010) · cites this paper as Shrout & Fleiss, 1979
In the citing paper
“ICC decomposes observed variance into between-query variance (task difficulty) and within-query variance (agent inconsistency), highlighting whether reported results reflect true capability or measurement noise.”
From Stochasticity in Agentic Evaluations: Quantifying Inconsistency with Intraclass Correlation (2025) · cites this paper as Shrout and Fleiss 1979
In the citing paper
“The ICC quantifies the proportion of total variance attributable to differences between tasks and can be understood as a function of both the difficulty of the dataset (variance between tasks) and the consistency of the agent (variance within tasks).”
From Stochasticity in Agentic Evaluations: Quantifying Inconsistency with Intraclass Correlation (2025) · cites this paper as Shrout and Fleiss 1979
In the citing paper
“Reproducibility of the final placenta, fetus and amniotic fluid volume in millilitres was assessed using the ICC (2,1) [37], [38] for inter-observer repeatability between the semi-automated Random Walker results, regarded as the ground-truth used for performance evaluation, and the newly generated FCNN outputs.”
From Fully Automated 3-D Ultrasound Segmentation of the Placenta, Amniotic Fluid, and Fetus for Early Pregnancy Assessment (2021) · cites this paper as [37]
Citations
Cites
Coefficient Alpha and the Internal Structure of Tests
Cronbach, L. J. (1951) · Psychometrika · doi:10.1007/bf02310555 · Cited by 43,931
Statistical principles in experimental design.
Winer, B. J. (1962) · McGraw-Hill Book Company · doi:10.1037/11774-000 · Cited by 27,137
Rozeboom, W. W., Lord, F. M., Novick, M. R., & Birnbaum, A. (1969) · American Educational Research Journal · doi:10.3102/00028312006001112 · Cited by 8,013
Rozeboom, W. W., Lord, F. M., Novick, M. R., & Birnbaum, A. (1969) · American Educational Research Journal · doi:10.2307/1162101 · Cited by 8,012
Snedecor, G. W., & Cochran, W. G. (1967) · Cited by 6,573
Scheffé, H. (1960) · Soil Science · doi:10.1097/00010694-196006000-00016 · Cited by 5,625
An Approximate Distribution of Estimates of Variance Components
Satterthwaite, F. E. (1946) · Biometrics Bulletin · doi:10.2307/3002019 · Cited by 4,373
The Intraclass Correlation Coefficient as a Measure of Reliability
Bartko, J. (1966) · Psychological Reports · doi:10.2466/pr0.1966.19.1.3 · Cited by 2,206
Statistics for the social sciences
Hays, W. L. (1973) · Medical Entomology and Zoology · Cited by 2,081
The theory of the estimation of test reliability
Kuder, G. F., & Richardson, M. W. (1937) · Psychometrika · doi:10.1007/bf02288391 · Cited by 1,953
Cited by
Sorted by citations
Items 21,801–21,900 of 23,883
Türk Romatoid Artrit Hastalarının Hastalıkları Hakkındaki Farkındalık Düzeyi
Bozbaş, G. T., & Gurer, G. (2018) · DergiPark (Istanbul University)
Evaluation methods of sagittal curvatures in invasive examinations of the spine: a systematic review
Marchetti, B., Raupp, E. G., & Candotti, C. T. (2020) · Ciência em Movimento · doi:10.15602/1983-9480/cm.v22n44p3-20
Inclusive Classroom Profile Training Program
West, T., Soukakou, E. P., & Winton, P. J. (2021) · Infants & Young Children · doi:10.1097/iyc.0000000000000189
Tatebe, M., Morita, A., Kurahashi, T., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-257594/v1
Schwarz, J., Vidondo, B., Maninchedda, U. E., Sprick, M., Schöpfer, M. C., & Cruz, A. M. (2021) · Frontiers in Veterinary Science · doi:10.3389/fvets.2021.595455
Xu, Y., & Stocco, A. (2020) · Cognitive Science
Igwesi-Chidobe, C. N., Muomah, R. C., Sorinola, I. O., & Godfrey, E. L. (2021) · Research Square · doi:10.21203/rs.3.rs-292051/v1
عطاالله, م. ع. ا., فتحی, إ. ص., & بريقع, س. م. ج. (2021) · مجلة تطبیقات علوم الریاضة · doi:10.21608/jaar.2021.155957
Evaluation of the Psychometric Properties of the Scale A-ONE: An Italian Cross-Sectional Study
Cerone, M., Tofani, M., Fabbrini, G., Marcellini, G., Berardi, A., Conti, C., Santis, R. D., Valente, D., & Galeoto, G. (2021) · Occupational Therapy International · doi:10.1155/2021/8874953
Wrigley, T. V., Begg, R. K., Larcom, E., et al. (2013)
Validation of a Malay Version of the Patient-Rated Wrist Hand Evaluation (PRWHE-MV)
Teh, K. H., Saaid, F. M., Arumugam, M., et al. (2021) · IIUM Medical Journal Malaysia · doi:10.31436/imjm.v20i2.1545
Patel, S. P., Rozental, T. D., & Zurakowski, D. (2015) · The Journal Of Hand Surgery · doi:10.1016/j.jhsa.2015.01.028
Federalismo fiscal: la experiencia reciente de Oaxaca
Altamirano, D. C. (1999) · El economista mexicano
Influence of hormonal variations on the performance and pacing of female cyclists in the heat
Hutchins, K. P. (2021) · Queensland University of Technology · doi:10.5204/thesis.eprints.207214
A Brief Negotiation Interview Adherence Scale for Smoking Cessation: A psychometric evaluation
Pantalon, M. V., Dziura, J. D., Li, F., D’Onofrio, G., Weiss, J., & Bernstein, S. L. (2021) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2021.108398
Iyer, S. N., Pope, M. A., Taksal, A., Mohan, G., Rangaswamy, T., Loohuis, H., Shah, J. L., Joober, R., Schmitz, N., Ramachandran, P., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-388384/v1
Saleh, N. S., Marie, S., Grimon, G., et al. (2021) · Médecine Nucléaire · doi:10.1016/j.mednuc.2021.02.003
Appropriateness criteria for cardiac computed tomography
Desai, M. Y., & Schoenhagen, P. (2011)
Norwood, A. F., Linnan, L. A., Ammerman, A. S., et al. (2020) · doi:10.21203/rs.3.rs-31070/v1
Buescher, J., Weisrock, F., Fritschka, M., Beckmann, S., Litmeier, S., Tahirović, E., Radenovic, S., Busjahn, A., Krahn, T., Dinh, W., et al. (2021) · International Journal of Cardiovascular Research
Communication in married couples: Exploring the roles of betrayal and forgiveness
Frousakis, N. N. (2010)
Evidence for the Dispersed Leadership Theory in Teams: A Policy-Capturing Study
Konradt, U., Garbers, Y., Hoch, J. E., & Ellwart, T. (2014) · Multimedialen Archiv und Publikationsserver der Christian-Albrechts-Universität zu Kiel (Christian-Albrechts-Universität zu Kiel)
postprint - Predicting Sign Learning in Hearing AdultsPreprint
Martinez, D., & Singleton, J. L. (2020) · doi:10.31234/osf.io/zynwf
Suss, J., & Petushek, E. J. (2021) · Criminologie · doi:10.7202/1076695ar
Clackson, K., Pohran, N., Galli, R. M., Labno, L., Farias, M., Bekinschtein, T. A., & Noreika, V. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01632-3
An Overview of Resting State Functional Connectivity Studies of Major Depressive Disorder
Chase, H. W. (2021) · Springer eBooks · doi:10.1007/978-3-030-59797-9_14
Hartung, F., Wang, Y., Mak, M., Willems, R. M., & Chatterjee, A. K. (2020) · doi:10.31234/osf.io/tuwmz
Nye, J. A., Piccinelli, M., Hwang, D., et al. (2021) · Journal of Nuclear Cardiology · doi:10.1007/s12350-021-02628-4
Toffaletti, J. G., Buckner, K. A., Liu, B., et al. (2021) · The Journal of Applied Laboratory Medicine · doi:10.1093/jalm/jfab029
Vinetti, G., Ferrarini, G., Taboni, A., et al. (2021) · Physiological Measurement · doi:10.1088/1361-6579/ac0a9b
Shrout, P. E., & Begg, M. D. (2014) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat04845
Self-citationTest-retest reliability of regression dynamic causal modelingPreprint
Frässle, S., & Stephan, K. E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.01.446526
Larsen, J. B. (2021) · VBN Forskningsportal (Aalborg Universitet) · doi:10.5278/vbn.phd.med.00138
Surviving and prospering in challenging business environments
Siebelink, R. (2020) · doi:10.3990/1.9789036549813
Assessing human morphology using statistical shape analysis
Thelwell, M. (2020) · Sheffield Hallam University · doi:10.7190/shu-thesis-00369
Xu, C., Yin, M., & Mo, W. (2020) · Research Square · doi:10.21203/rs.3.rs-56740/v1
CACTUS: A Digital Tool for Quality Assurance, Education and Evaluation in Surgical Pathology
Aksaç, A., Demetrick, D. J., Box, A. H., et al. (2021) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-021-00643-x
Using formulaic sequences in improving EFL students' written fluency By
Falah, A. (2020) · KU ScholarWorks (The University of Kansas) · doi:10.13140/rg.2.2.29611.77607
A Cognitive Information Theory of Music: A Computational Memetics Approach
Chan, T.-S. T. (2008) · Goldsmiths (University of London) · doi:10.25602/gold.00028791
An Evaluation of the Practice Element Response Form in a Sample of Preservice Trainees
Maesaka, T. J., Shernoff, E. S., & Nakamura, B. J. (2021) · Evidence-Based Practice in Child and Adolescent Mental Health · doi:10.1080/23794925.2021.1941428
Iwamoto, H., & Suzuki, H. (2021) · Cogent Economics & Finance · doi:10.1080/23322039.2021.1954764
Marfisi, D., Tessa, C., Marzi, C., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-798103/v1
Projection scrubbing: a more effective, data-driven fMRI denoising methodPreprint
Pham, D., McDonald, D. J., Ding, L., Nebel, M. B., & Mejia, A. F. (2021) · arXiv (Cornell University)
Flores‐Rodrigo, D., Meza‐Mauricio, J., Retamal‐Valdes, B., et al. (2021) · International Journal of Dental Hygiene · doi:10.1111/idh.12545
Lamb, T. (2018) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3vq2ss4c
Pedraza, D. F. (2021) · Cadernos Saúde Coletiva · doi:10.1590/1414-462x202129020107
Filho, A. C. D. S. S., Simozo, F. H., & Murta, L. O. (2021) · Research on Biomedical Engineering · doi:10.1007/s42600-021-00168-x
Boggs, A. E., Schmitt, L., McLane, R. D., Adayev, T., LaFauci, G., Dominick, K. C., Gross, C., Horn, P. S., & Erickson, C. A. (2021) · Research Square · doi:10.21203/rs.3.rs-850436/v1
Rauner, F. (2021) · Technical and vocational education and training · doi:10.1007/978-981-16-0957-2_6
Jiang, L., Xia, Y., Wang, L., et al. (2021) · doi:10.5194/acp-2021-533-rc1
Stenberg, G. (2021) · Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems · doi:10.1075/is.18044.ste
Yu, S. (2021) · doi:10.5194/acp-2021-533-ac3
Chen, Y., & Atwood, M. E. (2008) · iDEA - Drexel University Institutional Repository · doi:10.17918/etd-2978
Yu, S. (2021) · doi:10.5194/acp-2021-533-ac4
Reliability of Echocardiographic Measurements in Infants Exposed to Zika Virus.Preprint
Orofino, D. H. G., Passos, S. R. L., Leite, M. D. F. M. P., et al. (2020) · Research Square · doi:10.21203/rs.3.rs-38421/v1
Human Behavior Prediction for Risk Analysis
Szekeres, A., & Snekkenes, E. A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86970-0_21
Tanaka, F., Umino, M., Maeda, M., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-944191/v1
Applying Statistical Models to Health Outcomes For Australian Patients with Bronchiectasis
Kingkam, P. (2021) · UTS ePRESS (University of Technology Sydney)
Ibarra-Benítez, M. B., Caballero-Contrera, A. E., Páez-Reyes, L. F., et al. (2021) · International journal of odontostomatology · doi:10.4067/s0718-381x2021000300653
Diffeomorphic Alignment of Along-Tract Diffusion Profiles from Tractography
Lee, D. S., Sahib, A. K., Kubicki, A., et al. (2021) · Mathematics and visualization · doi:10.1007/978-3-030-73018-5_5
Brain Connectivity: Exploring from a High-Level Topological Perspective
Sheng, W., Li, L., Han, S., Fan, Y., Wang, C., Tang, Q., Chen, Y., Cui, Q., & Chen, H. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87358-5_2
Ryder, C., Mackean, T., Coombes, J., Hunter, K., Ullah, S., Rogers, K. D., Essue, B. M., Holland, A. J. A., & Ivers, R. (2021) · Australian Health Review · doi:10.1071/ah20299_co
Reliability of the submaximal iSTEP performance test in children with haemophilia
Chugh, D., Thorpe, N., Alderson, L. M., et al. (2021) · Haemophilia · doi:10.1111/hae.14436
Body composition assessment of premature infants in the neonatal intensive care unit
Nagel, E. (2019) · University of Minnesota Digital Conservancy (University of Minnesota)
Los sustantivos abstractos en la escritura y evaluación de textos académicos
López, E. M. G., & Neve, L. J. A. (2020) · Enunciación · doi:10.14483/22486798.16688
Unger, J. P. (2012) · Publication Server of the University of Education Heidelberg (University of Education Heidelberg)
Occupant monitoring, modelling, and simulation to improve office design and operation
Gilani, S. (2017) · Carleton University's Institutional Repository (MacOdrum Library, Carleton University) · doi:10.22215/etd/2017-12142
Individual Differences in Social Cognition and Behavior: a Personality Psychology Framework
Blain, S. D. (2021) · University of Minnesota Digital Conservancy (University of Minnesota)
Objective questionnaires for assessment sleep quality
Streiner, D. L. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-85235-7.00007-7
Bissessar, C. S. (2021) · Springer eBooks · doi:10.1007/978-3-030-76591-0_1
Well-being adjusted health expectancy - a new summary measure of population health
Muszyńska, M. M., & Luy, M. (2021) · doi:10.1553/0x003cb424
The Validity and Reliability of Immersive VR Device in Measuring Craniocervical Range of Motion.Preprint
Yan, C., Wang, H., Wu, T., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-958939/v1
Vedaei, F., Alizadeh, M., Romo, V. M., Mohamed, F. B., & Wu, C. (2021) · Research Square · doi:10.21203/rs.3.rs-992129/v1
Skeletal muscle mass in head and neck cancer patients
Bril, S. I. (2021) · doi:10.33540/1001
Delivering Task-Based Language Teaching at Scale
Nielson, K. B. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.020
Designing a Classroom-Based Task-Based Language Assessment Framework for Primary Schools
Gorp, K. V. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.033
Developing a Task-Based Approach
Oliver, R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.006
Gurzynski‐Weiss, L., Giacomino, L., & Jarrett, D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.032
Blustery with an Occasional Downpour
Maie, R., & Salen, B. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.011
Task-Based Language Teaching and Indigenous Language Revitalisation
Riestenberg, K. J., & Sherris, A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.021
Task-Based Language Teaching in a Japanese University
Lambert, C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.008
Test-retest reliability of regression dynamic causal modeling
Frässle, S., & Stephan, K. E. (2022) · Zurich Open Repository and Archive (University of Zurich) · doi:10.3929/ethz-b-000532266
Training for Tasks the Cooperative Way
McMillan, N., & Jordan, G. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108868327.028
Memory, dementia, and the functional role of the parietal cortex
Seibert, T. M. (2011) · eScholarship (California Digital Library)
Metadata
- Authors
- Shrout, P. E., & Fleiss, J. L.
- Affiliations
- Columbia University (US)
- ORCID
- Shrout, Patrick E.
- Venue
- Psychological Bulletin
- Published
- 1979
- Volume
- 86
- Issue
- 2
- Pages
- 420-428
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2141403362
- Cited by
- 24,532
- References
- 20
- Citations by year
- 2026: 1452 · 2025: 1085 · 2024: 998 · 2023: 1023 · 2022: 1083 · 2021: 1379 · 2020: 1189 · 2019: 1116 · 2018: 1178 · 2017: 1113 · 2016: 1106 · 2015: 1057 · 2014: 1172 · 2013: 1044 · 2012: 914
- FWCI
- 13.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Bulletin (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Multidisciplinary Science and Engineering Research
- Keywords
- intraclass correlation coefficient, rater reliability, inter-rater reliability, reliability coefficients, confidence intervals, multiple raters
- MeSH terms
- Humans, Reproducibility of Results, Models, Statistical
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
