On Strategies for Comparing Occupational Exposure Data to Limits

Abstract

Parametric statistical approaches to assessing workplace exposure levels have typically focused either on the probability that a single measurement exceeds a limit or on whether the mean exposure for a population of workers exceeds a limit. This article reviews and clarifies some methods that have been proposed for each of these two approaches, on the assumption that the exposure data represent a random sample from a lognormal distribution. For tests concerning the mean exposure level, the authors developed a potentially useful new procedure based on a bound for noncentral t critical values. Appropriate sample size calculation are emphasized, and computer simulation is used to compare competing methods for assessing mean exposure. The authors conclude that the new proposed method offers an appealing alternative to existing methods in many cases. The importance of employiong an exposure assessment strategy that is is concert with underlying etiologic consideration is stressed.