Power Testing of Graphical Methods for identification of Outliers in Poisson Regression Model Article Swipe
Zawar Hussain
,
Atif Akbar
,
Ibrahim Nafisah
,
Mohammed M. A. Almazah
,
Mohammed Alshahrani
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4375014/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4375014/v1
This paper investigates the structure and utility of partial residual (PRES), augmented partial residual (APRES), and conditional expectation and residuals (CERES) plots for visualising influence diagnostics as a function of chosen predictors in the context of generalised linear models (GLMs). Here, predictor transformation is used to analyse Poisson regression as GLM, and PRES, APRES, and CERES plots are created. Due to the behaviour of the response variable and the linked link function with various variables, these plots' effectiveness in creating a strong visual impression may vary. In comparison to other approaches, PRES, CERES (L), and CERES (K) exhibit the highest power for influence diagnostics, according to the power of the tests for various plots.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4375014/v1
- https://www.researchsquare.com/article/rs-4375014/latest.pdf
- OA Status
- gold
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396886181
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396886181Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-4375014/v1Digital Object Identifier
- Title
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Power Testing of Graphical Methods for identification of Outliers in Poisson Regression ModelWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-14Full publication date if available
- Authors
-
Zawar Hussain, Atif Akbar, Ibrahim Nafisah, Mohammed M. A. Almazah, Mohammed AlshahraniList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-4375014/v1Publisher landing page
- PDF URL
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https://www.researchsquare.com/article/rs-4375014/latest.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-4375014/latest.pdfDirect OA link when available
- Concepts
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Outlier, Poisson regression, Identification (biology), Regression analysis, Computer science, Statistics, Poisson distribution, Regression, Econometrics, Mathematics, Data mining, Medicine, Biology, Population, Environmental health, BotanyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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23Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.predictors | 32 |
| abstract_inverted_index.regression | 49 |
| abstract_inverted_index.variables, | 75 |
| abstract_inverted_index.approaches, | 91 |
| abstract_inverted_index.conditional | 17 |
| abstract_inverted_index.diagnostics | 26 |
| abstract_inverted_index.expectation | 18 |
| abstract_inverted_index.generalised | 37 |
| abstract_inverted_index.visualising | 24 |
| abstract_inverted_index.diagnostics, | 104 |
| abstract_inverted_index.investigates | 3 |
| abstract_inverted_index.effectiveness | 78 |
| abstract_inverted_index.transformation | 43 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.13067881 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |