The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Sample size formulas for estimating intraclass correlation coefficients with precision and assurance
Abstract
The number of subjects required to estimate the intraclass correlation coefficient in a reliability study has usually been determined on the basis of the expected width of a confidence interval. However, this approach fails to explicitly consider the probability of achieving the desired interval width and may thus provide sample sizes that are too small to have adequate chance of achieving the desired precision. In this paper, we present a method that explicitly incorporates a prespecified probability of achieving the prespecified width or lower limit of a confidence interval. The resultant closed‐form formulas are shown to be very accurate. Copyright © 2012 John Wiley & Sons, Ltd.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
Forming inferences about some intraclass correlation coefficients.
McGraw, K. O., & Wong, S. P. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.1.30 · Cited by 6,903
Two-sided confidence intervals for the single proportion: comparison of seven methods
Newcombe, R. G. (1998) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19980430)17:8<857::aid-sim777>3.0.co;2-e · Cited by 5,107
THE USE OF CONFIDENCE OR FIDUCIAL LIMITS ILLUSTRATED IN THE CASE OF THE BINOMIAL
CLOPPER, C. J., & PEARSON, E. S. (1934) · Biometrika · doi:10.1093/biomet/26.4.404 · Cited by 5,003
The Intraclass Correlation Coefficient as a Measure of Reliability
Bartko, J. J. (1966) · Psychological Reports · doi:10.2466/pr0.1966.19.1.3 · Cited by 2,299
Statistical Methods for Research Workers.
I., L., & Fisher, R. A. (1926) · Journal of the Royal Statistical Society · doi:10.2307/2341488 · Cited by 2,128
Interval estimation for the difference between independent proportions: comparison of eleven methods
Newcombe, R. G. (1998) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19980430)17:8<873::aid-sim779>3.0.co;2-i · Cited by 1,851
Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed
Kottner, J., Audige, L., Brorson, S., Donner, A., Gajewski, B. J., Hróbjartsson, A., Roberts, C., Shoukri, M., & Streiner, D. L. (2011) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2011.01.016 · Cited by 997
Sample size requirements for estimating intraclass correlations with desired precision
Bonett, D. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1108 · Cited by 987
Cited by
Mobile app rating scale: a new tool for assessing the quality of health mobile apps
Stoyanov, S. R., Hides, L., Kavanagh, D. J., Zelenko, O., Tjondronegoro, D., & Mani, M. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3422 · Cited by 2,233
Ashbaugh, A. R., Houle-Johnson, S., Herbert, C., El-Hage, W., & Brunet, A. (2016) · PLOS ONE · doi:10.1371/journal.pone.0161645 · Cited by 625
Baumel, A., Faber, K., Mathur, N., Kane, J. M., & Muench, F. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7270 · Cited by 206
“In line with a previous examination in this field [11], a minimum sample size of 41 was required to establish with 87% assurance whether true interrater reliability lay within 0.15 of a sample observation of 0.80 [47,48].”
InfluentialChow, H.-W., & Yang, C.-C. (2020) · JMIR mHealth and uHealth · doi:10.2196/14707 · Cited by 140
“Based on the formula proposed by Zou [43], the number of participants (n) required for achieving a target power of 0.90 was 8.”
Influential
Metadata
- Authors
- Zou, G. Y.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2012-07-04
- Volume
- 31
- Issue
- 29
- Pages
- 3972-3981
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2091019309
- Cited by
- 466
- References
- 24
- FWCI
- 11.67
- Type
- journal article
- Language
- en
- Open access
- closed
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
