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.

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.
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DOI:
10.1038/s41370-021-00331-7
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发表时间:
2021-11
影响因子:
4.5
通讯作者:
Zhu B
Zhu B
中科院分区:
医学3区
文献类型:
--
作者:
Friesen MC;Choo-Wosoba H;Sarazin P;Hwang J;Dopart P;Russ DE;Deziel NC;Lavoué J;Albert PS;Zhu B

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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. We used semi-continuous models to identify time and industry trends in 52,457 OSHA inspection lead sample results. The first component of the semi-continuous model predicted the probability of detecting concentrations ≥0.007 mg/m3 (highest estimated detection limit, 62% of measurements). The second component predicted the median concentration of measurements ≥0.007 mg/m3. Both components included a random-effect for industry and fixed-effects for year, industry group, analytical method, and other variables. We used the two components together to predict median industry- and time-specific lead concentrations. The probabilities of detectable concentrations and the median detected concentrations decreased with year; both were also lower for measurements analyzed for multiple (vs. one) metals and for those analyzed by inductively-coupled plasma (vs. atomic absorption spectroscopy). The covariance was 0.30 (standard error=0.06), confirming the two components were correlated. We identified determinants of exposure in data with over 60% left-censored, while accounting for correlated relationships and without assuming a distribution for the censored data.
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