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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...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2023
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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 |
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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 |