Sentence examples for models with exposure from inspiring English sources

Chi-square tests for trend were used for all exposure response models with exposure levels assigned 0, 1, and 2 for nonexposed, ≤ the median, and > the median.

To evaluate possible departure from linearity, likelihood ratio tests were used to compare the fit of models with exposure quintile as a categorical variable versus quintile as a linear term.

Addition of each of the thyroid hormones (TSH, T3, total T4, free T4 or T3-uptake) separately to models with exposure group, age, BMI group, and lipids did not change the exposure relationships with diabetes (not shown).

Associations that were significant at the p < 0.05 level in models with exposure represented as a continuous (log-transformed) variable we further examined by substituting tertiles of the biomarkers (micrograms per gram creatinine) to assess the linearity of the effects.

However, for the 362 women of questionnaire-identified races other than white, we observed positive, statistically significant associations with employment duration and cumulative exposure; only smoking, birth cohort, and self- or proxy questionnaire completion had statistically significant explanatory power when added to models with exposure metrics.

23 Because of the uncertainty regarding the time window over which past glucocorticoid exposure may affect the current risk of serious infection, six alternative WCD models with exposure time windows corresponding to previous 1 or 3 months, or 1, 2, 3 or 4 years were fitted.

To increase power, the associations between exposures and behavioural outcomes were also examined using linear regression models with exposures categorized into tertiles as well as a continuous variable.

To explore the shape of the dose response curves, we estimated associations between average PM10 concentrations over different lags and the microcirculation markers estimated using unadjusted models with exposures modeled as restricted cubic splines with 5 knots at the 5th, 25th, 50th, 75th, and 95th percentiles (Harrell 2001).

We also ran a model with exposure to cat allergen as a covariate and stratified the model according to measured exposure to cat allergens.

Consider a regression model with exposure X and true confounder Z, that is, Instead of the true confounder Z, we observe an error-prone proxy variable V.

33 34 We estimated the propensity score using a logistic regression model with exposure to a specialist team as the independent variable.