Journal article
0300 The NIEHS GuLF STUDY: A comparison of the β-substitution method and a Bayesian approach for handling highly censored measurement data
Occupational and environmental medicine (London, England), v 71(Suppl 1), pp A104-A104
Jun 2014
Abstract
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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Details
- Title
- 0300 The NIEHS GuLF STUDY: A comparison of the β-substitution method and a Bayesian approach for handling highly censored measurement data
- Creators
- Tran Huynh - University of MinnesotaHarrison Quick - University of MissouriGurumurthy Ramachandran - University of MinnesotaSudipto Banerjee - University of MinnesotaJoao Monteiro - Product Innovation and Engineering (United States) (United States, Saint James) - LLCCaroline Groth - University of MinnesotaMark Stenzel - Product Innovation and Engineering (United States) (United States, Saint James) - LLCAaron Blair - National Cancer InstituteDale Sandler - University of North Carolina at Chapel HillLawrence Engle - University of North Carolina at Chapel HillRichard Kwok - National Institute of Environmental Health SciencesPatricia Stewart - Product Innovation and Engineering (United States) (United States, Saint James) - LLC
- Publication Details
- Occupational and environmental medicine (London, England), v 71(Suppl 1), pp A104-A104
- Publisher
- British Medical Journal (BMJ)
- Number of pages
- 1
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics; Environmental and Occupational Health
- Other Identifier
- 991019335486504721