Sentence examples for model after adjusting from inspiring English sources

SHRs were attenuated in the multivariable adjusted model after adjusting for conventional risk factors for diabetes and psychological stress, but a significantly higher risk was still observed in unskilled and semiskilled workers (SHR 1.39; 95% CI 1.08 1.78).

In order to evaluate the trends of screening pattern in each independent variable which were statistically significant in multivariable logistic analysis, the adjusted mean was calculated on the basis of the linear regression model after adjusting for other independent variables.

The only sociodemographic factor that was significant was marital status, but it did not enter into the final model after adjusting for other significant correlates.

Logistic analysis revealed that the rs116806486 polymorphism remained associated with LOAD in a dominant model, whereas the rs6691117 polymorphism was associated with LOAD in additive and recessive models but not in a dominant model after adjusting for sex, age at onset, and APOE ε4 status.

So we calibrate the model's trend lines to better match estimates from the group of nonpartisan pollsters who were on average within plus-or-minus one percentage point of the trend lines generated by the HuffPost 2012 model after adjusting the model to the actual election results.

These results are confirmed by the bootstrap estimates of the robust regression model after adjusting for hospital characteristics.

The odds ratio (OR) and 95% confidence interval (CI) was calculated in unadjusted and multivariate-adjusted models after adjusting for age, income status, education status, marital status, job status, drinking status, hypertension, diabetes mellitus, cerebrovascular disease (CVD), BMI, and physical activity.

P # means P values were calculated by deviance analysis for logistic regression model after adjusted for gender and age.

The rs17740607 polymorphism showed replicated associations with all-cause CHF according to genotype and allele distribution and also under a dominant and additive genetic model after adjusted for traditional cardiovascular-related factors.

In logistic regression models after adjusting for confounding variables (e.g., age, initial electrocardiographic rhythm, and initiation of basic life support), hospital admission and discharge rates did not differ significantly.

In multivariable logistic regression analysis, the relationship between migraine and EDS was weaker than in bivariate analysis, while the pattern of increasing OR for EDS with increasing headache frequency persisted in models after adjusting for age, BMI, depression, and gender (Table 4).