1
Multivariate logistic regression analysis was used to define risk factors for infection.
2
Multivariable logistic regression analysis was used to identify predictors of 30-day mortality.
3
Associations between diseases and exposures were studied using multiple logistic regression analysis.
4
Cox regression models and logistic regression analysis were used for statistical analyses.
5
Univariate and subsequent logistic regression analysis with bootstrap resampling have been used.
6
Results from this were collated for statistical multiplexing using logistic regression analysis.
7
Groups were compared by using weighted chi-square tests and logistic regression analysis.
8
Then a diagnostic model was developed based on the logistic regression analysis.
9
Multiple logistic regression analysis was performed to identify anti-HDV positivity independent predictors.
10
A multivariate logistic regression analysis was performed to analyze adjusted in-hospital mortality.
11
Tumor size was the strongest predictor of conversion on logistic regression analysis.
12
A binary logistic regression analysis was performed to detect predictors for SMOTs.
13
The forecast and actual 6-month outcomes were compared by logistic regression analysis.
14
Determinants of malnutrition were entered into a multivariate logistic regression analysis model.
15
Predictors of blood pressure control were assessed using multiple logistic regression analysis.
16
Multivariable logistic regression analysis was performed to identify predictors of graft failure.