The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Regression through the Origin
Abstract
Summary: This article describes situations in which regression through the origin is appropriate, derives the normal equation for such a regression and explains the controversy regarding its evaluative statistics. Differences between three popular software packages that allow regression through the origin are illustrated using examples from previous issues of Teaching Statistics.
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
Champernowne, D. G., & Theil, H. (1972) · The Economic Journal · doi:10.2307/2230222 · Cited by 2,115
Methods and applications of linear models: regression and the analysis of variance
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3361 · Cited by 350
Test Statistics for Mixture Models
Marquardt, D. W., & Snee, R. D. (1974) · Technometrics · doi:10.1080/00401706.1974.10489234 · Cited by 96
Errors in Computer Packages. Least Squares Regression Through the Origin
Gordon, H. (1981) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2987701 · Cited by 23
Cited by
Understanding bland altman analysis
Giavarina, D. (2015) · Biochemia Medica · doi:10.11613/bm.2015.015 · Cited by 4,022
Introductory Statistics with R
(2002) · Statistics and Computing · doi:10.1007/b97671 · Cited by 730
The predictability of extinction: biological and external correlates of decline in mammals
Cardillo, M., Mace, G. M., Gittleman, J. L., Jones, K. E., Bielby, J., & Purvis, A. (2008) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2008.0179 · Cited by 435
Mattes, R. D., Shikany, J. M., Kaiser, K. A., & Allison, D. B. (2011) · Obesity Reviews · doi:10.1111/j.1467-789x.2010.00755.x · Cited by 160
Metadata
- Authors
- Eisenhauer, J. G.
- Venue
- Teaching Statistics
- Publisher
- Wiley
- Published
- 2003-06-24
- Volume
- 25
- Issue
- 3
- Pages
- 76-80
- ISSN
- 0141-982X (ISSN-L)
- 1467-9639
- OpenAlex
- W2058013657
- Cited by
- 381
- References
- 4
- FWCI
- 1.96
- 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: Regression through the Origin. https://app.cochat.ai/papers/10.1111/1467-9639.00136
- The paper
- Eisenhauer, J. G. (2003). Regression through the Origin. Teaching Statistics. https://doi.org/10.1111/1467-9639.00136
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.