Objectives Over 150 000 measurements taken on workers responding to the 2010 Deepwater Horizon oil spill are being used to develop exposure estimates for the participants in the GuLF STUDY. A large portion of the measurements, however, has values below the limit of detection (left-censored). The β-substitution method has been shown to provide accurate estimates for handling censored data, but a comparison to a Bayesian method, which permits the estimation of uncertainty and accounts for prior information, is currently lacking. The goal of this research was to compare the two methods.
Method Each method was challenged with computer-generated datasets drawn from lognormal distributions with the geometric mean (GM) = 1, sample sizes = 5–100, geometric standard deviation (GSD) = 2–5, and percent censoring = 10–90%. Percent bias and coverage (the percentage of 95% uncertainty intervals containing the truth) were used as evaluation metrics.
Results For most of our simulation scenarios, estimates of bias from the β-substitution and Bayesian methods were generally comparable for the AM and GM. The β-substitution was generally less biassed in estimating the GSD and the 95th percentile than the Bayesian method. The Bayesian method provided consistently better coverage for the AM than β-substitution. It also provided uncertainty estimates the GM, GSD, and the 95th percentile while β-substitution does not.
Conclusions The β-substitution method generally was observed to have little bias but it only allows the calculation of uncertainty estimates around the AM. The Bayesian approach provided reasonably accurate point and interval estimates (i.e., coverage), but this comes with the cost of additional computation.
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