The DOI matches its Crossref record.
Calculation of polychotomous logistic regression parameters using individualized regressions
Abstract
The use of individualized logistic regression, in which a series of separate simple logistic regression analyses are performed as a replacement for polychotomous logistic regression, is studied. The asymptotic relative efficiencies of the individual parameter estimates are observed to be generally high, as are the efficiencies of predicted probability estimates and, to a somewhat lesser extent, joint tests of parameters from different regressions.
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
Eagly, A. H., Nater, C., Miller, D. I., Kaufmann, M., & Sczesny, S. (2020) · American Psychologist · doi:10.1037/amp0000494 · Cited by 1,136
Frequency of obsessive-compulsive disorder in a community sample of young adolescents
VALLENI-BASILE, L. A., GARRISON, C. Z., JACKSON, K. L., WALLER, J. L., McKEOWN, R. E., ADDY, C. L., & CUFFE, S. P. (1994) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-199407000-00002 · Cited by 468
Statistical assessment of ordinal outcomes in comparative studies
Scott, S. C., Goldberg, M. S., & Mayo, N. E. (1997) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(96)00312-5 · Cited by 337
ORDINAL REGRESSION MODELS FOR EPIDEMIOLOGIC DATA
ARMSTRONG, B. G., & SLOAN, M. (1989) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115109 · Cited by 320
Frair, J. L., Merrill, E. H., Visscher, D. R., Fortin, D., Beyer, H. L., & Morales, J. M. (2005) · Landscape Ecology · doi:10.1007/s10980-005-2075-8 · Cited by 276
Metadata
- Authors
- BECG, C. B., & GRAY, R.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1984
- Volume
- 71
- Issue
- 1
- Pages
- 11-18
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2085641264
- Cited by
- 298
- References
- 0
- FWCI
- 3.93
- 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: Calculation of polychotomous logistic regression parameters using individualized regressions. https://app.cochat.ai/papers/10.1093/biomet/71.1.11
- The paper
- BECG, C. B., & GRAY, R. (1984). Calculation of polychotomous logistic regression parameters using individualized regressions. Biometrika. https://doi.org/10.1093/biomet/71.1.11
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.
