Sentence examples for model namely age from inspiring English sources

Odds ratios and P values computed by the logistic regression analysis were obtained while including potential confounding factors in the model, namely age, sex and smoking.

Moreover, the PA comprises all the predictors reported by Slaven et al. [ 31] in their model, namely age, gender and BMI, thus pointing towards the importance of these factors for prediction of hip arthroplasty results.

There were 7 variables entered into the prediction model, namely, age (X1), gender (X2), education (X3), type of flood (x5), severity of flood (X6), flood experience (X7), and mental status before flood (X8).

All the variables with p value of less than 0.2 in the age adjusted model, namely age, sex, family history of diabetes, education level, BMI 25 29.9 and ≥ 30 kg/m2, abdominal obesity, hypertension, high TG, low HDL-C, IFG, IGT and IFG/IGT were selected to enter into the final model.

In step 3, three control variables were included in the model, namely, gender, age, and number of concomitant diseases.

A number of covariates that were hypothesized to be associated with both sociodemographic characteristics and health media use were included in the models namely sex, age, marital status, employment, rural/urban residence, health insurance, presence of children under age 18 in the household, having had cancer, and having had a family member with cancer.

Unlike the other examples, the actual vector-space of demographic time shown in Brinks et al. (2014) Fig. 2 only identifies a subset of the times-measures implied by the model of the authors, namely age (y-axis), period (x-axis), birth cohort (implied by a linear combination of age and period) and duration of disease (z axis).

The reduced model identified two useful predictors; namely, age at delivery, and whether an individual was on insulin or not during pregnancy.

We controlled for biological susceptibility factors [ 11], namely age and gender (Model 1), and then additionally controlled for potential cardiovascular risk and extrinsic susceptibility factors including education, smoking, pack-years, SHS, BMI, and waist circumference (Model 2).

All models accounted for important confounding factors, namely age, total body fat percentage, socioeconomic status (NZDep2006), physical activity levels (IPAQ), and the amount of saturated fat consumed.

Odds ratios and confidence intervals were calculated using multivariable logistic regression models after accounting for potential confounders namely age, maternal smoking and Indigenous status which can affect maternal and foetal outcomes [ 10- 13].