Sentence examples for multiple exposure variables from inspiring English sources

Also, multiple exposure variables were collected, which allowed us to begin examining the larger relationships that exist among multiple variables.

Several works in the past have used factor analysis, a key component and the measurement model part of structural equation models, to relate multiple exposure variables with health variables.

Strengths include the use of an objective measure of physical activity in a large population-based sample of children living in heterogeneous environments and the inclusion of multiple exposure variables to assess the relative importance of different correlates.

As such, we were able to focus on the distinct qualitative differences in CAPs content and avoid uncertainties of multiple exposures to variable PM concentrations and components.

By overlaying disease outcome with exposure variables, multiple data sets can be integrated to identify trends, degree of synchronization [ 6] between exposures and outcomes, or even synchronization between two outcomes such as mortality and co-morbidity.

The ability to detect statistically significant associations was limited by the small sample size including participants with a wide age distribution, as well as by exposure variables with multiple strata and adjustment for multiple co-factors.

We imputed missing values for all baseline and interim exposure variables using multiple imputation (N = 5).

First, by using a Bayesian mixture framework developed for the analysis of correlated exposure variables in multiple logistic regression (de Vocht et al, 2012).

The correlation between PCDD/PCDF indoor air exposure and PCDD/PCDF blood concentrations was examined by linear multiple regression analysis considering different exposure variables and taking confounders into account.

To further provide visual representation of the dose response curve, we fitted restricted cubic spline models by including transformed variables of exposure variables to multiple logistic regression models (with 2 knots at the 33.3th and 67.7th percentiles) with adjustment for covariates included in Model 3 [ 24].

Change in FEV1 residual from 1991 to 2000 was modelled in relation to the exposure variables using multiple linear regression, controlling for the effect of smoking and number of pack-years of cigarettes in 2000 and for Carstairs deprivation score as recorded at baseline.