Scaling for residual variance components of ordered category responses in generalised linear mixed multilevel models
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It is not currently possible to accurately estimate how much of the change in higher-level variance is caused by real changes in variance and how much is caused by the constrained level 1 variance.
“It is not currently possible to accurately estimate how much of the change is caused by real changes in variance and how much is caused by the constrained level 1 variance (Yang M, University of Nottingham, 2012, personal communication).”
From Evaluating Long-term Outcomes of NHS Stop Smoking Services (ELONS): a prospective cohort study (2015) · cites this paper as [39]
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Self-citation
- Authors
- Fielding, A.
- Corresponding author
- Fielding, Antony
- Venue
- Quality and Quantity
- Published
- 2004-08
- Volume
- 38
- Issue
- 4
- Pages
- 425-433
- ISSN
- 0033-5177 (ISSN-L)
- 1573-7845
- OpenAlex
- W2008004264
- Cited by
- 27
- References
- 7
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2016: 4 · 2015: 1 · 2014: 2 · 2013: 1 · 2012: 2
- FWCI
- 1.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Quality & Quantity (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- ordered categorical responses, ordinal data, generalized linear mixed models, multilevel models, random effects, model extension
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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.
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