Rh. Lyles et al., A LOGNORMAL DISTRIBUTION-BASED EXPOSURE ASSESSMENT METHOD FOR UNBALANCED DATA, The Annals of occupational hygiene, 41(1), 1997, pp. 63-76
We present a generalization of existing statistical methodology for as
sessing occupational exposures while explicitly accounting for between
- and within-worker sources of variability. The approach relies upon a
n intuitively reasonable model for shift-long exposures, and requires
repeated exposure measurements on at least some members of a random sa
mple of workers from a job group. We make the methodology more readily
applicable by providing the necessary details for its use when the ex
posure data are unbalanced (that is, when them are varying numbers of
measurements per worker). The hypothesis testing strategy focuses on t
he probability that an arbitrary worker in a job group experiences a l
ong-term mean exposure above the occupational exposure limit (OEL). We
also provide a statistical approach to aid in the determination of an
appropriate intervention strategy in the event that exposure levels a
re deemed unacceptable for a group of workers. We discuss important pr
actical considerations associated with the methodology, and we provide
several examples using unbalanced sets of shift-long exposure data ta
ken on workers in various sectors of the nickel-producing industry. We
conclude that the statistical methods discussed afford sizable practi
cal advantages, while maintaining similar overall performance to that
of existing methods appropriate for balanced data only. (C) 1997 Briti
sh Occupational Hygiene Society.