Cargando…

Trend detection with non-detects in long-term monitoring, a mixed model approach

In long-term monitoring of contaminants in biota, a common approach is to use yearly geometric means of measured concentrations in sampled individuals as a basis for trend analysis. When some or all measurements in a particular year are reported as non-detects, it is unclear how to proceed in calcul...

Descripción completa

Detalles Bibliográficos
Autor principal: Sköld, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182149/
https://www.ncbi.nlm.nih.gov/pubmed/37171495
http://dx.doi.org/10.1007/s10661-023-11285-8
_version_ 1785041728996114432
author Sköld, Martin
author_facet Sköld, Martin
author_sort Sköld, Martin
collection PubMed
description In long-term monitoring of contaminants in biota, a common approach is to use yearly geometric means of measured concentrations in sampled individuals as a basis for trend analysis. When some or all measurements in a particular year are reported as non-detects, it is unclear how to proceed in calculating the yearly mean. I argue that by casting the problem in terms of a mixed model, non-detects can be accounted for using statistical techniques for censored data. The approach is illustrated using data from the Swedish national monitoring programme for contaminants in biota. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10661-023-11285-8.
format Online
Article
Text
id pubmed-10182149
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-101821492023-05-14 Trend detection with non-detects in long-term monitoring, a mixed model approach Sköld, Martin Environ Monit Assess Research In long-term monitoring of contaminants in biota, a common approach is to use yearly geometric means of measured concentrations in sampled individuals as a basis for trend analysis. When some or all measurements in a particular year are reported as non-detects, it is unclear how to proceed in calculating the yearly mean. I argue that by casting the problem in terms of a mixed model, non-detects can be accounted for using statistical techniques for censored data. The approach is illustrated using data from the Swedish national monitoring programme for contaminants in biota. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10661-023-11285-8. Springer International Publishing 2023-05-12 2023 /pmc/articles/PMC10182149/ /pubmed/37171495 http://dx.doi.org/10.1007/s10661-023-11285-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Sköld, Martin
Trend detection with non-detects in long-term monitoring, a mixed model approach
title Trend detection with non-detects in long-term monitoring, a mixed model approach
title_full Trend detection with non-detects in long-term monitoring, a mixed model approach
title_fullStr Trend detection with non-detects in long-term monitoring, a mixed model approach
title_full_unstemmed Trend detection with non-detects in long-term monitoring, a mixed model approach
title_short Trend detection with non-detects in long-term monitoring, a mixed model approach
title_sort trend detection with non-detects in long-term monitoring, a mixed model approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182149/
https://www.ncbi.nlm.nih.gov/pubmed/37171495
http://dx.doi.org/10.1007/s10661-023-11285-8
work_keys_str_mv AT skoldmartin trenddetectionwithnondetectsinlongtermmonitoringamixedmodelapproach