Simulation-based assessment of model selection criteria during the application of benchmark dose method to quantal response data Article Swipe
Keita Yoshii
,
Hiroshi Nishiura
,
Kaoru Inoue
,
Takayuki Yamaguchi
,
Akihiko Hirose
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1186/s12976-020-00131-w
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1186/s12976-020-00131-w
Background To employ the benchmark dose (BMD) method in toxicological risk assessment, it is critical to understand how the BMD lower bound for reference dose calculation is selected following statistical fitting procedures of multiple mathematical models. The purpose of this study was to compare the performances of various combinations of model exclusion and selection criteria for quantal response data. Methods Simulation-based evaluation of model exclusion and selection processes was conducted by comparing validity, reliability, and other model performance parameters. Three different empirical datasets for different chemical substances were analyzed for the assessment, each having different characteristics of the dose-response pattern (i.e. datasets with rich information in high or low response rates, or approximately linear dose-response patterns). Results The best performing criteria of model exclusion and selection were different across the different datasets. Model averaging over the three models with the lowest three AIC (Akaike information criteria) values (MA-3) did not produce the worst performance, and MA-3 without model exclusion produced the best results among the model averaging. Model exclusion including the use of the Kolmogorov-Smirnov test in advance of model selection did not necessarily improve the validity and reliability of the models. Conclusions If a uniform methodological suggestion for the guideline is required to choose the best performing model for exclusion and selection, our results indicate that using MA-3 is the recommended option whenever applicable.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s12976-020-00131-w
- https://tbiomed.biomedcentral.com/track/pdf/10.1186/s12976-020-00131-w
- OA Status
- hybrid
- Cited By
- 4
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3047601127
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- OpenAlex ID
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https://openalex.org/W3047601127Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s12976-020-00131-wDigital Object Identifier
- Title
-
Simulation-based assessment of model selection criteria during the application of benchmark dose method to quantal response dataWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-08-04Full publication date if available
- Authors
-
Keita Yoshii, Hiroshi Nishiura, Kaoru Inoue, Takayuki Yamaguchi, Akihiko HiroseList of authors in order
- Landing page
-
https://doi.org/10.1186/s12976-020-00131-wPublisher landing page
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https://tbiomed.biomedcentral.com/track/pdf/10.1186/s12976-020-00131-wDirect link to full text PDF
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YesWhether a free full text is available
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-
hybridOpen access status per OpenAlex
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https://tbiomed.biomedcentral.com/track/pdf/10.1186/s12976-020-00131-wDirect OA link when available
- Concepts
-
Akaike information criterion, Benchmark (surveying), Model selection, Selection (genetic algorithm), Reliability (semiconductor), Statistics, Computer science, Data mining, Mathematics, Econometrics, Machine learning, Quantum mechanics, Geodesy, Geography, Physics, Power (physics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
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2025: 2, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
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39Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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