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Bulletin of informatics and cybernetics
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DETERMINING THE NO-OBSERVED-ADVERSE-EFFECT LEVEL IN CATEGORICAL DATA

descriptionPublicationkeyboard_double_arrow_right Article English Journal:DETERMINING THE NO-OBSERVED-ADVERSE-EFFECT LEVEL IN CATEGORICAL DATA, volume 26, pages 141-152 (issn: 0286-522X, Copyright policy )

handle: https://hdl.handle.net/2324/13439

DETERMINING THE NO-OBSERVED-ADVERSE-EFFECT LEVEL IN CATEGORICAL DATA

Abstract

We discuss the determination of the no-observed-adverse-effect level (NOAEL) from a categorical data. Recently a method which incorporated the order regtriction into the multiple testing was proposed in Brown and Erdreich [2]. The test is an exact test and computation ally involved for large samples. Therefore we propose an alternative test which is competitive to their test and is easily used for large samples.

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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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