Publikation:
Better define beta-optimizing MDD (minimum detectable difference) when interpreting treatment-related effects of pesticides in semi-field and field studies

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dc.contributor.authorAlalouni, Urwa
dc.contributor.authorDuquesne, Sabine
dc.contributor.authorEgerer, Sina Elisabeth
dc.contributor.authorFrische, Tobias
dc.contributor.authorGergs, René
dc.contributor.authorGräff, Thomas
dc.contributor.authorSahm, René
dc.contributor.authorPieper, Silvia
dc.contributor.authorWogram, Jörn
dc.date.accessioned2024-06-16T14:04:42Z
dc.date.available2024-06-16T14:04:42Z
dc.date.issued2020
dc.description.abstractThe minimum detectable difference (MDD) is a measure of the difference between the means of a treatment and the control that must exist to detect a statistically significant effect. It is a measure at a defined level of probability and a given variability of the data. It provides an indication for the robustness of statistically derived effect thresholds such as the lowest observed effect concentration (LOEC) and the no observed effect concentration (NOEC) when interpreting treatment-related effects on a population exposed to chemicals in semi-field studies (e.g., micro-/mesocosm studies) or field studies. MDD has been proposed in the guidance on tiered risk assessment for plant protection products in edge of field surface waters (EFSA Journal 11(7):3290, 2013), in order to better estimate the robustness of endpoints from such studies for taking regulatory decisions. However, the MDD calculation method as suggested in this framework does not clearly specify the power which is represented by the beta-value (i.e., the level of probability of type II error). This has implications for the interpretation of experimental results, i.e., the derivation of robust effect values and their use in risk assessment of PPPs. In this paper, different methods of MDD calculations are investigated, with an emphasis on their pre-defined levels of type II error-probability. Furthermore, a modification is suggested for an optimal use of the MDD, which ensures a high degree of certainty for decision-makers. © 2020 Springer Nature Switzerland AGen
dc.format.extent1 Onlineresource (8814-8821)
dc.format.mediumonline resource
dc.identifier.doihttps://doi.org/10.60810/openumwelt-1785
dc.identifier.urihttps://openumwelt.de/handle/123456789/4162
dc.language.isoeng
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectUmweltrisikobewertung
dc.titleBetter define beta-optimizing MDD (minimum detectable difference) when interpreting treatment-related effects of pesticides in semi-field and field studies
dc.title.alternativeBetter define beta-optimizing MDD (minimum detectable difference) when interpreting treatment-related effects of pesticides in semi-field and field studies
dc.typeWissenschaftlicher Artikel
dc.type.dcmitext
dc.type.mediumcomputer
dspace.entity.typePublication
local.bibliographicCitation.journalTitleEnvironmental science and pollution research
local.bibliographicCitation.originalDOI10.1007/s11356-020-07761-0
local.bibliographicCitation.volume27 (2020)
local.collectionAufsätze
local.contributor.authorId02185030
local.contributor.authorId(DE-588)1059727757
local.contributor.authorId(DE-588)175690766
local.contributor.authorId(DE-588)1083787748
local.contributor.authorId(DE-588)128759690
local.identifier.catalogId02477086
local.ingest.leader07031naa a2200000uu 4500
local.jointTitleBETTER DEFINE BETAOPTIMIZING MDD MINIMUM DETECTABLE DIFFERENCE WHEN INTERPRETING TREATMENTRELATED EFFECTS OF PESTICIDES IN SEMIFIELD AND FIELD STUDIES
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