Examples of using Logistic regression model in English and their translations into Portuguese
{-}
-
Colloquial
-
Official
-
Medicine
-
Financial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
-
Official/political
Table VI shows the multivariate logistic regression model when assessing the influence of the study parameters PSS cardiac risk and blood glucose level against postoperative complications.
Table VII shows the multivariate logistic regression model in the assessment of physical status and PSS cardiac risk against the incidence of deaths.
The logistic regression model was used to identify the independent variables associated with the neonatal death outcome.
We used a logistic regression model to identify variables that can predict the outcome of SUI.
To construct the multiple logistic regression model, the stepwise forward method was used,
The logistic regression model showed that the chance of having pain decreased almost 5% with every hour elapsed following delivery.
The Hosmer-Lemeshow test was used under the hypothesis that the multiple logistic regression model presents a well fit value p 0.8705.
The multiple logistic regression model showed an independent association of sociodemographic variables,
The logistic regression model Table 3 with all predictors was statistically significant x28, N 430 97.81, p.
Using a logistic regression model, those researchers observed that use of long-term oxygen therapy
The logistic regression model shows a significant association of triglycerides,
The Hosmer-Lemeshow test indicated that the logistic regression model was a good fit for the data p=0.7125.
To be included in the adjustment stage of the logistic regression model, the variables need to present association p.
Multivariate analysis was performed using a logistic regression model and the stepwise technique.
A logistic regression model was used to control for confounders and estimate measures of effect odds ratio[OR] and their related 95% confidence intervals 95%CI.
Subsequently, the independent variables were adjusted from a non-conditional multiple logistic regression model of hierarchical structure to control confounding factors.
The multinomial logistic regression model enabled to disaggregate functional capacity into more than two categories.
a multiple logistic regression model was created including those variables that in univariate analyses had p.
The multiple logistic regression model was also not significant with motivator for exercise practice p=0.053,