Sentence examples for model variables associated from inspiring English sources

Logistic regression was used to model variables associated with undetectable RNA PCR viral load.

In this setting, we have selected for the started model variables associated with prognosis, with a P-value less than or equal to 0.20 in univariate analyses.

The results of sensitivity analysis are shown in Fig. 4 for the three model variables associated with the observables in the experimental data and using the parameters in Table 1.

The logistic regression model for variables associated with hypovolemia showed that the following variables: heart rate, respiratory rate, systolic blood pressure, mean arterial pressure, CVP, and IJV collapsibility index were all significant (p < 0.05) (Table 3).

In multivariate model, independent variables associated with anemia were moderate disease activity and CRP.

In the Cox proportional hazards model of variables associated with TTP, 43 patients were included.

For the final model, only variables associated to empowerment with p < 0.25 were included.

Each multivariable model included variables associated with HIV infection in any of the three bivariate scenarios at P < 0.10.

For each category of variables, this resulted in a logistic regression model presenting variables associated with work disability at 24 months of sick leave.

We included in our model all variables associated with death on univariate analysis (p<0.15) controlling for age group, race, and sex.

We followed the recommendation from Ramirez-Valles et al 30 to perform regression analysis on unweighted data and include in the model all variables associated to network size (education and frequency of Internet use, according to Kruskal-Wallis rank test).