This paper demonstrates statistical methods that estimate measurement error
from available industrial hygiene data. Errors in measuring a continuous e
xposure variable may arise when all individuals in a work area are assigned
the same exposure. An example is when the mean of exposure measurements ob
tained on a sample of individuals is assigned to all workers with similar j
obs. This may lead to inaccurate point and interval estimates in exposure-r
esponse modeling. A method of simulating the distribution of true (i.e., un
observed) individual exposures is described in order to estimate the mean a
nd variance of measurement error. The minimum variance unbiased estimator a
pproximates the mean of lognormally distributed exposure measurements. The
distribution of true individual exposures is approximated by the distributi
on of simulated estimates of mean exposure. The methodology is illustrated
by exposure data from work areas manufacturing refractory ceramic fiber (RC
F) and RCF products. Results show that exposure is slightly underestimated
in work areas with between 25 and 113 exposure measurements; measurement er
ror variance averages about 1.3% of the total variance.