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A unified model for covariate measurement error adjustment in an occupational health study while accounting for non-detectable exposures

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The paper focuses on an occupational health study where the goal is to associate a worker's true log-normal-scale mean dust exposure over the year with forced expiratory volume. A previous analysis used repeated shift-long dust exposure measurements, taken over a year, as a surrogate to address the issue of the mean exposure being unobservable. However, in this study the associated measurement error is further complicated by the fact that some exposure measurements fall below a detectable limit. We extend the previous analysis via full maximum likelihood, to account appropriately for non-detectable exposures.
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Keywords: Bias; Detection limit; Log-normal distribution; Maximum likelihood

Document Type: Research Article

Affiliations: Emory University, Atlanta, USA

Publication date: 2005-01-01

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