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Risk assessments for pesticides and other plant protection products (PPPs) often use models to estimate the exposure of different population groups.
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This model was re-estimated using a complex samples logistic regression model to estimate the effect of each predictor on SHS exposure (Table 4).
We used an excess relative risk (ERR) model to estimate the ERR per unit of arsenic exposure.
They used an environmentally attributable fraction model to estimate the damages done by exposure to anthropogenic sources of mercury.
These data were used in a model to estimate the overall time-weighted-average vapor exposure for jobs based on estimates of task exposures and their duration.
We used geospatial models to estimate ambient BC and represent personal exposures of traffic-related pollution.
In part, our motivation was to use this model to estimate exposures in the context of an environmental epidemiology investigation.
Therefore, a model to estimate past exposure was derived [ 31].
Multivariable linear regression models were used to estimate the effects of each individual PM2.5 component exposure on CIMT.
propagating uncertainties (material, model and environmental exposure) throughout the reduced model in order to estimate the probability of corrosion initiation using surrogate modeling techniques; and.
Regression logistic model was used to estimate the strength of association between birth defect and ARV trimester exposure.
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