Sentence examples for mean exposure estimates from inspiring English sources

PM10, SO2, NO2 daily mean exposure estimates were used.

For all air pollutants, with the exception of ozone, daily mean exposure estimates were used.

The second scenario resulted in approximately 16 19% lower mean exposure estimates for those less than 30 years of age.

These metrics included: the same day exposure, 1, 2 and 3 day lagged exposures, as well as cumulative 3-day and 5-day mean exposure estimates.

Bland Altman plots [see Supplemental Material, Figure 1 (doi:10.1289/ehp.0901509)] showed that the difference between the two models increased with mean exposure estimates.

Many studies have focused on long-term arithmetic mean exposure estimates based on small time scale (short-term) observations and assuming lognormal RF to model exposure distributions (Clayton et al. 1999; Wallace and Williams 2005).

A general formula for determining the variance of this group mean exposure estimate,, has been proposed and applied by several authors [ 12, 23, 44, 47].

Due to autocorrelation, the observed variance of a mean exposure estimate was also larger than expected from theoretical formulae based on the posture variance components.

Amandus and Wheeler (1987) studied the mortality experience through 1981 of 575 white men with mean exposure estimated at 200 fibers/cc-years, who were hired at Libby before 1970 and worked at least 1 year.

Regardless of which mean exposure estimate was used (P*P, P*D or PD), in scenarios that involved a PF of 0.82, a high priority for risk reduction was demonstrated for younger age groups.

Generalized formulae are available for estimating statistical efficiency, i.e. the relationship between the precision of a mean exposure estimate, on the one hand, and, on the other, the size of relevant variance components, and the number of measurements at the corresponding sampling stages [ 23, 24].