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Hazard ratio (HR) was estimated by the Cox proportional hazards model using age as timescale, and compared using paired homogeneity test.
In order to determine the extent to which age alone can discriminate between "poor-drivers" and "not-poor-drivers", a logistic regression model using age as a predictor was developed (Eq. 3) and was subjected to diagnostic checks/goodness-of-fit test and confirmed through model validation.
Tables 1, 2, 3 summarize the association of β-AR genotypes with HRV indices determined by a GLM model using age, gender, and BMI as covariates.
Backwards elimination was used to select the model using age group, sex, and race and ethnicity.
In our analysis, the model using age and the Gail RR had poor calibration, and therefore the AUC estimates are not meaningful.
A simple prognostic model using age and BMI at booking could be used for selective screening of GDM in Vietnam and in other low- and middle-income settings.
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The Cox model used age as the underlying time variable.
The basic model used age and ICD-10 code only.
Our BC incidence model uses age, CFR, PM50 and year of birth to estimate the number of BC incident cases by age and cohort of birth.
The DIETRON model uses age- and gender-specific estimates of relative risks drawn from meta-analyses of trials, cohort studies and case control studies.
The full model used age, International Classification of Disease (ICD-10) code, known malignancy, physiological variables and routine blood data to predict 7-day mortality.
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