Open AccessSimultaneous modeling of detection rate and exposure concentration using semi-continuous models to identify exposure determinants when left-censored data may be a true zero
Author(s) -
Melissa C. Friesen,
Hyoyoung ChooWosoba,
Philippe Sarazin,
Joo-Yeon Hwang,
Pamela J. Dopart,
Daniel Russ,
Nicole C. Deziel,
Jérôme Lavoué,
Paul S. Albert,
Bin Zhu
Publication year - 2021
Publication title -
journal of exposure science and environmental epidemiology/journal of exposure science and environmental epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.155
H-Index - 92
eISSN - 1559-064X
pISSN - 1559-0631
DOI - 10.1038/s41370-021-00331-7
Subject(s) - statistics , analyte , confidence interval , mathematics , distribution (mathematics) , covariance , analytical chemistry (journal) , chemistry , econometrics , chromatography , mathematical analysis
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.