A Comparison of the β-Substitution Method and a Bayesian Method for Analyzing Left-Censored Data.

ABSTRACT: Classical statistical methods for analyzing exposure data with values below the detection limits are well described in the occupational hygiene literature, but an evaluation of a Bayesian approach for handling such data is currently lacking. Here, we first describe a Bayesian framework for analyzing censored data. We then present the results of a simulation study conducted to compare the β-substitution method with a Bayesian method for exposure datasets drawn from lognormal distributions and mixed lognormal distributions with varying sample sizes, geometric standard deviations (GSDs), and censoring for single and multiple limits of detection. For each set of factors, estimates for the arithmetic mean (AM), geometric mean, GSD, and the 95th percentile (X0.95) of the exposure distribution we

SUBMITTER: Huynh T 

PROVIDER: S-EPMC4715251 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature