Sentence examples for model subjects with from inspiring English sources

In a competing risks regression model, subjects with no primary care physician visits in the year prior to the index event were significantly more likely to have the outcome of interest.

Under the dominant model, subjects with genotype g = AA or Aa are genetically susceptible, that is, they are at either increased or decreased risk compared to the baseline group (g = aa).

In the fully adjusted model, subjects with 25(OH D deficiency had a 54% increased likelihood of albuminuria compared to those without deficiency (OR 1.54, 95% CI 1.14-2.07, p = 0.006).

In the multivariable logistic regression model, subjects with RA had significantly greater odds of needing help with personal care than subjects without arthritis and those with OA (p < 0.01).

In the fully adjusted model, subjects with 19 or fewer teeth without dentures had a 2.50 (95% CI 1.21 to 5.17 -fold increased risk for incident falls compared with those having 20 or more teeth(Table 2).

In an unadjusted model, subjects with the first (OR 3.46, 95% CI, 2.01-5.96) and second (OR 1.85, 95% CI, 1.08-3.18) tertile of CTRP-3 levels had significantly higher risk for CAD compared to those with the third tertile.

As is standard practice in regression models, subjects with missing values for any independent variable in a regression model were excluded from that specific analytic model.

In both the unadjusted and age/gender-adjusted models, subjects with poor sleep quality type were likely to go to bed late at night, wake up late, sleep for short time and less frequently had breakfast.

In separate multivariate models, subjects with worse VA engaged in less daily MVPA (11% less MVPA per 0.1 logMAR increment, 95% CI = −7 to −16%, p < 0.001), as did subjects with worse CS (13% less MVPA per 0.1 log CS decrement, 95% CI = −9 to −18%, p < 0.001).

In a crude, unadjusted logistic regression model (model 1) subjects with preDM and T2DM had approximately 4- and 6-fold increased odds of OSA compared with the normoglycemic group (Table 4).

To interact with the model, subjects seat in front of the robot and hold the robot's end effector.