Publication: New method for imputation of unquantifiable values using Bayesian statistics for a mixture of censored or truncated distributions: application to trace elements measured in blood of Olive Ridley sea turtles from Mexico
Authors
Salvat-Leal, Inmaculada ; Cortés-Gómez, Adriana A. ; Girondot, Marc ; Romero García, Diego
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Publisher
MDPI
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DOI
https://doi.org/10.3390/ani12212919
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info:eu-repo/semantics/article
Description
©2022 The authors. This manuscript version is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
This document is the Published version of a Published Work that appeared in final form in Animals. To access the final edited and published work see https://doi.org/10.3390/ani12212919
Abstract
One recurring difficulty in ecotoxicological studies is that a substantial portion of concentrations are below the limits of detection established by analytical laboratories. This results
in censored distributions in which concentrations of some samples are only known to be below a
threshold. The currently available methods have several limitations because they cannot be used with
complex situations (e.g., different lower and upper limits in the same dataset, mixture of distributions,
truncation and censoring in a single dataset). We propose a versatile method to fit the most diverse
situations using conditional likelihood and Bayesian statistics. We test the method with a fictive
dataset to ensure its correct description of a known situation. Then we apply the method to a dataset
comprising 25 element concentrations analyzed in the blood of nesting marine turtles. We confirm
previous findings using this dataset, and we also detect an unexpected new relationship between
mortality and strontium concentration
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Citation
Animals, 2022. Vol. 12, N. 21, 2919 .
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Este ítem está sujeto a una licencia Creative Commons. http://creativecommons.org/licenses/by/4.0/