The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Generalized linear models for the analysis of taguchi‐type experiments
Abstract
Recent interest in Taguchi's methods have led to developments in joint analysis of the mean and dispersion from designed experiments. A commonly used method is the analysis of variance of the transformed data. However, a single transformation cannot necessarily produce the Normality, constancy of variance and linearity of systematic effects for the mean and dispersion models. We describe the use of generalized linear models for the analysis of such experiments and illustrate the methods with a data set.
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
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Self-citationQuasi-likelihood functions, generalized linear models, and the Gauss—Newton method
WEDDERBURN, R. W. M. (1974) · Biometrika · doi:10.1093/biomet/61.3.439 · Cited by 2,122
Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments
Daniel, C. (1959) · Technometrics · doi:10.1080/00401706.1959.10489866 · Cited by 798
Cited by
Khuri, A. I., & Mukhopadhyay, S. (2010) · WIREs Computational Statistics · doi:10.1002/wics.73 · Cited by 2,113
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
Yang, Y., & Land, K. C. (2016) · Chapman & Hall/CRC eBooks · doi:10.1201/b13902 · Cited by 280
Metadata
- Authors
- Nelder, J. A., & Lee, Y.
- Venue
- Applied Stochastic Models and Data Analysis
- Publisher
- Wiley
- Published
- 1991-03
- Volume
- 7
- Issue
- 1
- Pages
- 107-120
- ISSN
- 1099-0747 (ISSN-L)
- 8755-0024
- OpenAlex
- W320578018
- Cited by
- 179
- References
- 3
- FWCI
- 6.53
- 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: Generalized linear models for the analysis of taguchi‐type experiments. https://app.cochat.ai/papers/10.1002/asm.3150070110
- The paper
- Nelder, J. A., & Lee, Y. (1991). Generalized linear models for the analysis of taguchi‐type experiments. Applied Stochastic Models and Data Analysis. https://doi.org/10.1002/asm.3150070110
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.
