Simultaneous modeling of detection rate and exposure concentration using semi-continuous models to identify exposure determinants when left-censored data may be a true zero

BACKGROUND: Most methods for treating left-censored data assume the analyte is present but not quantified. Biased estimates may result if the analyte is absent such that the unobserved data represents a mixed exposure distribution with an unknown proportion clustered at zero. OBJECTIVE: We used semi...

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Detalles Bibliográficos
Autores principales: Friesen, Melissa C., Choo-Wosoba, Hyoyoung, Sarazin, Philippe, Hwang, Jooyeon, Dopart, Pamela, Russ, Daniel E., Deziel, Nicole C., Lavoué, Jérôme, Albert, Paul S., Zhu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8595485/
https://www.ncbi.nlm.nih.gov/pubmed/34006962
http://dx.doi.org/10.1038/s41370-021-00331-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8595485/
https://www.ncbi.nlm.nih.gov/pubmed/34006962
http://dx.doi.org/10.1038/s41370-021-00331-7

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