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Cited by 34Advanced Statistical Methods and ModelsStatistical Methods and Bayesian InferenceStatistical and numerical algorithms

The DOI matches its Crossref record; the references it cites are not checked yet.

Cook’s distance for generalized linear mixed models

Pinho, Luis Gustavo B., Nobre, Juvêncio S., Singer, Julio M.·2015·Computational Statistics & Data Analysis
DOI 10.1016/j.csda.2014.08.008
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References 42 · Cited by 34

Metadata

Authors
Pinho, L. G. B., Nobre, J. S., & Singer, J. M.
Affiliations
Universidade Federal do Ceará (BR)
Corresponding author
Nobre, Juvêncio S.
ORCID
Venue
Computational Statistics & Data Analysis
Publisher
Elsevier BV
Published
2015-02
Volume
82
Pages
126-136
ISSN
0167-9473 (ISSN-L)
DOI
10.1016/j.csda.2014.08.008
OpenAlex
W2039521816
Cited by
34
References
42
Citations by year
2026: 3 · 2025: 4 · 2024: 2 · 2023: 1 · 2022: 5 · 2021: 3 · 2020: 4 · 2019: 4 · 2018: 3 · 2016: 3 · 2015: 1
FWCI
1.41
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Computational Statistics & Data Analysis (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) (308613/2011-2)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Keywords
Cook's distance, generalized linear mixed models, influential observations, influence diagnostics, fixed effects estimation, first-order approximation

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CoChat. (2026). Citation check: Cook’s distance for generalized linear mixed models. https://app.cochat.ai/papers/10.1016/j.csda.2014.08.008
The paper
Pinho, L. G. B., Nobre, J. S., & Singer, J. M. (2015). Cook’s distance for generalized linear mixed models. Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2014.08.008

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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