2001
DOI: 10.1080/15298660108984622
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Exposure Estimation in the Presence of Nondetectable Values: Another Look

Abstract: A common problem faced by industrial hygienists is the selection of a valid way of dealing with those samples reported to contain nondetectable values of the contaminant. In 1990, Hornung and Reed compared a maximum likelihood estimation (MLE) statistical method and two methods involving the limit of detection, L. The MLE method was shown to produce unbiased estimates of both the mean and standard deviation under a variety of conditions. That method, however, was complicated, requiring difficult mathematical c… Show more

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Cited by 90 publications
(77 citation statements)
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“…Undetectable urinary 3-PBA concentrations were estimated as half the limit of detection (LOD) value (Finkelstein et al, 2001). …”
Section: Discussionmentioning
confidence: 99%
“…Undetectable urinary 3-PBA concentrations were estimated as half the limit of detection (LOD) value (Finkelstein et al, 2001). …”
Section: Discussionmentioning
confidence: 99%
“…Initially, 16 metrics were created from the transformed cortisol measurements to represent different aspects of the overall cortisol response. Seven metrics of biological plausibility were then selected for further analysis (Figure 1): pretest level (the first sample level), mean level (mean of all samples), area under the curve with respect to zero (AUC), 36 AUC with respect to baseline (AUC b ), variance (variance of all 4 samples), slope 12 (slope from samples 1-2), and slope 34 (slope from samples 3-4).…”
Section: Creation Of Cortisol Metricsmentioning
confidence: 99%
“…In the ÎČ-substitution method, the LOD is substituted with a data-dependent ÎČ-factor multiplied by the LOD (Ganser and Hewett, 2010). In the parametric ML method, the parameters are estimated by maximizing the likelihood function, which is a product of the probability density function (PDF) for the measurements greater than the LOD and the cumulative distribution function (CDF) for the measurements less than the LOD (Fisher,1925;Cohen, 1959Cohen, , 1961Finkelstein and Verma, 2001). Probability plot-based methods [also known as regression on order statistics (ROS) or log-probit regression (LPR)] computes the mean and standard deviation by fitting a linear regression of the log-transformed data versus their normal scores on a normal or lognormal probability plot (Kroll and Stedinger, 1996;Helsel and Cohen, 1988;Gilliom and Helsel, 1986).…”
Section: Introductionmentioning
confidence: 99%