Abstract
A generalization of a hypothesis testing procedure for assessing the mean of a lognormal distribution is discussed in the context of occupational hygiene. We consider inference about the probability that the mean exposure level for an arbitrary worker in a job group exceeds the occupational exposure limit (OEL) for the toxicant under study. The approach is based on the assumption that the logged exposures (n measurements on each of k workers) conform to the one-way random effects ANOVA model. We focus on adaptations of classical large sample-based testing procedures, and we compare their performances in a variety of settings with the help of simulated data. We also discuss practical issues, including sample size approximation and alternative testing recommendations in the event of a negative between-worker variance component estimate.
Published Version
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