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 23,801–23,883 of 23,883
PDB-Dialogue: A Scalable Benchmark for Personality Recognition in Multi-turn Dialogue
anonymouscommitter, Zhou, B., Shen, J., Dong, C., Li, Z., & Yu, L. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-6913-6_21
Srinivasa, A. C., & Patil, S. S. (2026) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-026-02364-6
A large-scale comparison of human and large language model raters in automated essay scoring
Ayar, Z., & Akçapınar, G. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2745111
del Toro, S. F., & Aranda-Ruiz, J. (2026) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2026.1950679
Mitchinson, C. J., Benitez, B., Kwak, M., Snell, E. R., Kuhn, A. N., & Bergstrom, H. C. (2026) · The Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000005686
Fabero‐Garrido, R., Aguilar‐Zafra, S., del Corral, T., et al. (2026) · Neurology Report · doi:10.1097/npt.0000000000000586
Beyond usability: Spatial learning across autonomy-structured browser-based 360° virtual exhibitions
Hsieh, T., & Sheu, K.-W. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101383
Zhang, S., Liu, Y., Shin, S.-Y., & Lee, H.-A. (2026) · Sensors · doi:10.3390/s26206628
Lin, C., Liu, I. T.-A., Chou, C.-H., et al. (2026) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss60577.2026.11731157
Kural, D., Türkmen, B., Argunsah, H., et al. (2026) · Life · doi:10.3390/life16101762
Cohen, O., Sutton, E. J., Young, R. J., et al. (2026) · NMR in Biomedicine · doi:10.1002/nbm.70428
Jiang, Z., Lv, C., Lv, F., Dai, L., Ma, W., Wu, J., Luo, W., 刘康迈, Rou, K., Xie, Z., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-10836583/v1
Stetzelberger, V. M., Brosio, E., Laurençon, J., et al. (2026) · Clinical Orthopaedics and Related Research · doi:10.1097/corr.0000000000004169
Dong, S., & Li, R. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1905573
Wu, J., Kasim, Z. M., & Razak, F. N. A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1951427
Ergınlı, M., & Sofuoğlu, S. D. (2026) · Wood Material Science and Engineering · doi:10.1080/17480272.2026.2752117
Topal, A., & Aylanç, N. (2026) · Clinical Imaging · doi:10.1016/j.clinimag.2026.110976
Merlet, A. (2026) · Research Square · doi:10.21203/rs.3.rs-11447587/v1
Lu, J.-X., Hou, C.-H., Hsiao, S.-J., & Tsai, L. (2026) · American Journal of Occupational Therapy · doi:10.1177/19437676261498879
Tang, Z., & Kirman, B. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2750678
Bersanov, R. U., Ibragimov, G. G., Маммедов, С. М., et al. (2026) · Stomatology · doi:10.17116/stomat202610505149
Kizilkaya, V., Aslanyürek, M., Aslanyürek, C., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-11174522/v1
da Silva, A. C., & Aily, J. B. (2026) · Journal of Bodywork and Movement Therapies · doi:10.1016/j.jbmt.2026.10.022
Lang, D., Fallo, X., & Bennett, H. (2026) · The Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000005691
Pavel, M. S. R., Anjum, N., Cordova, A., Quarles, J. P., & Mahmud, M. R. (2026) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3797867.3828977
Elst, Z. V., Ascherl, R., Beken, S., Glaser, K., Härtel, C., Klingenberg, C., Simons, S. S., Dreesen, E., Gijsen, M., Spriet, I., et al. (2026) · Archives of Disease in Childhood Fetal & Neonatal · doi:10.1136/archdischild-2026-331135
Decision safety in football passing: A reproducible metric from probabilistic option sets
Carrasquilla, L., Vargas, G., & Wightman, P. M. (2026) · International Journal of Sports Science & Coaching · doi:10.1177/17479541261495048
Azimi, M. S., Cheraghi, M., & Zaidi, H. (2026) · Medical Physics · doi:10.1002/mp.70731
Reyes, M. K. G., Lau, G., Tsai, M., Kasturiratna, K. T. A. S., & Hartanto, A. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100415
de Florès, R., Canada, K. L., Brown, T. I., Gervais, N. J., Maaß, A., Rådman, G., Shine, J. P., Tucker, H. S. G., Molloy, E. N., Adams, J. N., et al. (2026) · Hippocampus · doi:10.1002/hipo.70143 · Cited by 1
Wang, B., Zhang, C., Cai, Y., & Li, Z. (2026) · Behavior Research Methods · doi:10.3758/s13428-026-03212-9
Oudrhiri, F. E., Diria, G., Gaboun, F., et al. (2026) · European Journal of Agronomy · doi:10.1016/j.eja.2026.128376
Palacios-Flores, M. A., Ibáñez, M., Wang, Z. L., et al. (2026) · Arthroscopy Sports Medicine and Rehabilitation · doi:10.1002/ars2.70131
歩行時に股関節伸展角度の減少を呈した 人工股関節置換術術後症例に対する トレッドミルトレーニングの即時的効果
芥川, 知., 勇人, 榎., 智彦, 西., et al. (2006) · Medical Entomology and Zoology · doi:10.11542/icpt.4.31
Mordell, S. (2014) · Summit (Simon Fraser University)
Islam, N. Y. (2013) · VCU Scholars Compass (Virginia Commonwealth University) · doi:10.25772/tcfc-1263
Brain wiring and neuronal dynamics : advances in MR imaging of focal epilepsy
Besseling, R. M. H. (2014) · Research Publications (Maastricht University) · doi:10.26481/dis.20140404rb
Effect of age on visual dependence for spatial orientation and postural control
Lee, S. (2014) · Research Portal (King's College London)
Park, Y.-H. (2007) · Korean Journal of Sport Biomechanics · doi:10.5103/kjsb.2007.17.1.001
Data Driven Approaches to Testing Homogeneity of Intraclass Correlation Coefficients
Wu, B. (2022) · Digital Archive @ GSU · doi:10.57709/1665628
Flenthrope, J. L. (2008) · KU ScholarWorks (The University of Kansas)
Disagreement Plots and the Intraclass Correlation in Agreement Studies
Doi, S. A. R. (2013) · Springer series on epidemiology and public health · doi:10.1007/978-3-642-37131-8_3
Udofa, I. A. (2015) · D-Scholarship@Pitt (University of Pittsburgh)
Cognitive Style Diversity in Decision Making Teams
Mello, A. L. (2012)
Arnold, C. C. (2011) · VCU Scholars Compass (Virginia Commonwealth University) · doi:10.25772/ck4r-dq77
A partially-automated approach to the assessment of mathematics in higher education
Rowlett, P. (2013) · Nottingham Trent University's Institutional Repository (Nottingham Trent Repository)
Jones, J. (2015) · Queen Margaret University eTheses Repository
Cardiac Function and Obesity: Effects of Weight Loss
Myint, K. S. (2010) · UEA Digital Repository (University of East Anglia)
ATTACHMENT AND SELF-REGULATION: AN EXPLORATORY ANALYSIS OF A BEHAVIORAL INDEX OF DEACTIVATION
Guttman, J. S. (2009) · UA Campus Repository (The University of Arizona)
Characterizing the Implementation of CBT for Youth Anxiety
Smith, M. M. (2013) · VCU Scholars Compass (Virginia Commonwealth University) · doi:10.25772/tw4q-1j67
Diagnostic significance of phase spectrum in acoustic analysis of pathological voice
Samborska-Owczarek, A. (2010) · Pomiary Automatyka Kontrola
SOA based and Quality of Human-Centric Experiments - A Quasi-Experiment over Software Engineering
Chandra, B., & Perumal, S. M. (2014)
The impact of team social role performance on team cohesion and team performance
Lowman, G. H. (2015) · UTC Scholar (University of Tennessee at Chattanooga)
Doepel, M. (2011) · UTUPub (University of Turku)
Schneider, R. J., & JOHNSON, J. (2004) · PsycEXTRA Dataset · doi:10.1037/e423582005-001
The level of adoption of analytical tools
Barahona, I. (2013) · doi:10.5821/dissertation-2117-95272
IQ as a Predictor and Moderator of Children’s Mental Health Status
Mathiassen, B. (2015) · NORA - Norwegian Open Research Archives
King, C. R. (2014) · Loyola eCommons (Loyola University of Chicago)
Proving Intelligent Design by Examining Unconscious Decision Processes
Dubreuil, M. K., & Koliada, S. (2014)
Gugiu, M. R., & Gugiu, P. C. (2012) · SSRN Electronic Journal
Mediators of the relationship between person-organisation fit and individual outcomes
Hamdan, M. (2011) · Cited by 1
Changes in Running Gait Biomechanics Following Exercise Intervention Program in Older Runners
Fukuchi, R. (2013) · Libraries and Cultural Resources (University of Calgary) · doi:10.5072/prism/25250
Tremor: Natural Behaviour, Trial Design and Physiological Outcome Measures
Alusi, S. H., & Bain, P. G. (2001) · Springer eBooks · doi:10.1007/978-1-4471-3787-0_29
(2011) · Amsterdam UMC (VU Amsterdam) - Institutional Repository · Cited by 1,209
Friedman (2000) · doi:10.1002/1097-0029(20001001)51:1
Paul (2007) · doi:10.1044/1092-4388(2007/094
Abbeduto (2004) · doi:10.1352/0895-8017(2004)109
Orsmond, G. I., Seltzer, M. M., Krauss, M. W., & Hong, J. (2003) · American Journal on Mental Retardation · doi:10.1352/0895-8017(2003)108
Towards an understanding of physical activity in people with chronic low back pain
Griffin, D. W. (2013) · University of Limerick · doi:10.34961/7893 · Cited by 1
Hou, X., Xiao, B., Liu, H., & Mueller, S. (2026) · arXiv · doi:10.48550/arxiv.2606.05509
“(Shrout and Fleiss 1979), indicating excellent agreement between raters (ICC = 0.91).”
Influential
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