The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: An integrated alternative method of conducting null hypothesis statistical tests.
Abstract
Null hypothesis statistical testing (NHST) has been debated extensively but always successfully defended. The technical merits of NHST are not disputed in this article. The widespread misuse of NHST has created a human factors problem that this article intends to ameliorate. This article describes an integrated, alternative inferential confidence interval approach to testing for statistical difference, equivalence, and indeterminacy that is algebraically equivalent to standard NHST procedures and therefore exacts the same evidential standard. The combined numeric and graphic tests of statistical difference, equivalence, and indeterminacy are designed to avoid common interpretive problems associated with NHST procedures. Multiple comparisons, power, sample size, test reliability, effect size, and cause-effect ratio are discussed. A section on the proper interpretation of confidence intervals is followed by a decision rule summary and caveats.
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Statistical principles in experimental design.
Winer, B. J. (1962) · McGraw-Hill Book Company · doi:10.1037/11774-000 · Cited by 26,755
Statistical Methods for Research Workers
(1945) · American Journal of Clinical Pathology · doi:10.1093/ajcp/15.11.552b · Cited by 10,880
Philosophical transactions of the Royal Society of London. B
Press, H. (1886) · Cited by 10,080
Experimental Design: Procedures for the Behavioral Sciences
Kirk, R. (2013) · doi:10.4135/9781483384733 · Cited by 8,539
Statistical Methods for Psychology.
Gudgeon, A. C., & Howell, D. C. (1994) · The Statistician · doi:10.2307/2348956 · Cited by 8,278
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
Schmidt, F. L., & Hunter, J. E. (2015) · doi:10.4135/9781483398105 · Cited by 5,542
Experimental Design: Procedures for the Behavioral Sciences.
Addelman, S., & Kirk, R. E. (1969) · Journal of the American Statistical Association · doi:10.2307/2283497 · Cited by 5,159
A sharper Bonferroni procedure for multiple tests of significance
HOCHBERG, Y. (1988) · Biometrika · doi:10.1093/biomet/75.4.800 · Cited by 4,829
Statistical Principles in Experimental Design
Green, P. E., Winer, B. J., Brown, D. R., & Michels, K. M. (1992) · Journal of Marketing Research · doi:10.2307/3172747 · Cited by 4,333
Cited by
Ellis, P. D. (2010) · doi:10.1017/cbo9780511761676 · Cited by 2,461
Equivalence Testing for Psychological Research: A Tutorial
Lakens, D., Scheel, A. M., & Isager, P. M. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245918770963 · Cited by 1,560
Inference by Eye: Confidence Intervals and How to Read Pictures of Data.
Cumming, G., & Finch, S. (2005) · American Psychologist · doi:10.1037/0003-066x.60.2.170 · Cited by 1,449
Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation
Maxwell, S. E., Kelley, K., & Rausch, J. R. (2008) · Annual Review of Psychology · doi:10.1146/annurev.psych.59.103006.093735 · Cited by 542
A Comparison of Expert and Nonexpert Raters Using the Consensual Assessment Technique
Kaufman, J. C., Baer, J., Cole, J. C., & Sexton∗, J. D. (2008) · Creativity Research Journal · doi:10.1080/10400410802059929 · Cited by 374
Metadata
- Authors
- Tryon, W. W.
- Venue
- Psychological Methods
- Published
- 2001
- Volume
- 6
- Issue
- 4
- Pages
- 371-386
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2063686445
- Cited by
- 391
- References
- 85
- FWCI
- 4.09
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: An integrated alternative method of conducting null hypothesis statistical tests. https://app.cochat.ai/papers/10.1037/1082-989x.6.4.371
- The paper
- Tryon, W. W. (2001). Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: An integrated alternative method of conducting null hypothesis statistical tests. Psychological Methods. https://doi.org/10.1037/1082-989x.6.4.371
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.
