The DOI matches its Crossref record.
The two-sample trimmed t for unequal population variances
Abstract
The effect of nonnormality on the Weleh approximate degrees of freedom t test is demonstrated. A two-sample trimmed t statistic for unequal population variances is proposed and its performance is also evaluated in comparison to the Welch t test under normality and under long-tailed distributions. If the underlying distributions is long-tailed or contaminated with outliers, the trimmed t is strongly recommended.
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
Cited by
Robust statistical methods in R using the WRS2 package
Mair, P., & Wilcox, R. (2020) · Behavior Research Methods · doi:10.3758/s13428-019-01246-w · Cited by 1,082
Why Psychologists Should by Default Use Welch’s t-test Instead of Student’s t-test
Delacre, M., Lakens, D., & Leys, C. (2017) · International Review of Social Psychology · doi:10.5334/irsp.82 · Cited by 1,037
Modified t Tests and Confidence Intervals for Asymmetrical Populations
Johnson, N. J. (1978) · Journal of the American Statistical Association · doi:10.1080/01621459.1978.10480051 · Cited by 276
Brechter, J. H., & Powers, C. M. (2002) · Gait & Posture · doi:10.1016/s0966-6362(02)00090-5 · Cited by 274
Robust Statistical Methods for Empirical Software Engineering
Kitchenham, B., Madeyski, L., Budgen, D., Keung, J., Brereton, P., Charters, S., Gibbs, S., & Pohthong, A. (2017) · Empirical Software Engineering · doi:10.1007/s10664-016-9437-5 · Cited by 257
Metadata
- Authors
- YUEN, K. K.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1974
- Volume
- 61
- Issue
- 1
- Pages
- 165-170
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2079484991
- Cited by
- 486
- References
- 0
- FWCI
- 1.28
- 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: The two-sample trimmed t for unequal population variances. https://app.cochat.ai/papers/10.1093/biomet/61.1.165
- The paper
- YUEN, K. K. (1974). The two-sample trimmed t for unequal population variances. Biometrika. https://doi.org/10.1093/biomet/61.1.165
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.