Sentence examples for models after adjusting from inspiring English sources

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.

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).

This last study concludes that the two noncoding SNPs, rs35391 and rs28777, are in LD with each other and are not significant melanoma risk predictors in a multivariate logistic regression models after adjusting for rs16891982 (p.F374L).

Data were analyzed using logistic regression models after adjusting for potential confounders.

We estimated birth weights from these models after adjusting for covariates (model 1 and model 2) as described above.

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).

However, it lost its significance in multivariate logistic models after adjusted for mean HbA1c.

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.

CONCLUSIONS: In a single-site study, there were no statistically significant differences in important ED operational metrics between a physician in triage model and a rotational patient assignment model after adjusting for confounders.

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.