Sentence examples for multiple logistic regression examining from inspiring English sources

In standard multiple logistic regression examining the association between insurance status, age, gender, employment, presence of a secondary comorbid illness, HIV status, and mortality, the model containing all predictors was statistically significant (p<0.001).

We used multiple logistic regression to examine the relationship between sex hormone levels at examination 7 and incident metabolic syndrome at examination 8 in men free of metabolic syndrome at examination 7, adjusting for age and smoking.

Multiple logistic regression analyses examined the effects of 22 predictors on the course of depression (onset, improvement, stability).

We evaluated this criterion using multiple logistic regression to examine the association between each mediator and behavioral risk factor, controlling for sexual orientation.

To probe the influence of different learning strategies, we performed a multiple logistic regression, which examined the weight of influence of all possible combinations of recent choices and outcomes on current behavior across multiple changeable three-armed bandit tasks.

We used multiple logistic regression to examine admissions or visits to emergency departments for fall related injury, with data censored after 24 months or time of death, whichever came first.

We developed multi-level models separately for the north and south zones based on the results of multiple logistic regression to examine certain contextual factors associated with still birth, induced abortion and miscarriages.

Table 2 shows the result of a multiple logistic regression analysis to examine the factors related to the methodological quality.

Multiple logistic regression used to examine independent associations of GDM and obesity with macrosomia and CS.

Additional analyses were conducting using a multiple logistic regression model to examine the associations between the independent variables and high screen time (top quartile or ≥107 mins/day).

All variables with a p-value of <0.2 in univariate analysis were included in the multiple logistic regression model to examine independently associated risk factors for VRE colonisation.