The DOI matches its Crossref record.
Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach.
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
Villar, J., Ismail, L. C., Victora, C. G., Ohuma, E. O., Bertino, E., Altman, D. G., Lambert, A., Papageorghiou, A. T., Carvalho, M., Jaffer, Y. A., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60932-6 · Cited by 2,281
Papageorghiou, A. T., Ohuma, E. O., Altman, D. G., Todros, T., Ismail, L. C., Lambert, A., Jaffer, Y. A., Bertino, E., Gravett, M. G., Purwar, M., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)61490-2 · Cited by 870
Accounting for natural and extraneous variation in the analysis of field experiments
Gilmour, A. R., Cullis, B. R., Verbyla, A. P., & Verbyla, A. P. (1997) · Journal of Agricultural, Biological, and Environmental Statistics · doi:10.2307/1400446 · Cited by 752
On the use of generalized additive models in time-series studies of air pollution and health
Dominici, F. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf062 · Cited by 728
A review of spline function procedures in R
Perperoglou, A., Sauerbrei, W., Abrahamowicz, M., & Schmid, M. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-019-0666-3 · Cited by 585
Metadata
- Authors
- Best, D. J., Green, P. J., & Silverman, B. W.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1994-12
- Volume
- 50
- Issue
- 4
- Pages
- 1228
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2797463641
- Cited by
- 1,177
- References
- 0
- FWCI
- 10.80
- 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: Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach. https://app.cochat.ai/papers/10.2307/2533467
- The paper
- Best, D. J., Green, P. J., & Silverman, B. W. (1994). Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach. Biometrics. https://doi.org/10.2307/2533467
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.
