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The appropriate number of degrees of freedom was assessed by univariate analyses using analysis of variance.
In the present study, many available preoperative clinical and pathologic factors were investigated by univariate analyses using the Kaplan Meier method.
* P-values refer to univariate analyses Baseline characteristics in women and men with and without fractures were compared by univariate analyses, using Independent sample T-test for continuous variables and chi-square testing for categorical variables.
Factors associated with CBD stones were assessed by univariate analyses using the χ-test, and by multivariate logistic regression analysis with calculation of odds ratios and 95% confidence intervals (CIs).
Variables were compared between groups by univariate analyses using the log-rank test, and prognostic factors associated with survival were identified by multivariate analysis using the Cox proportional hazards model with stepwise regression.
Putative associations between underlying medical conditions and demographics were explored by univariate analyses using admission to the ICU as the dependent variable, and are described in Additional file 2. The H1N1 positive patients admitted to the ICU tended to be younger, have a higher heart rate, and had a higher Body Mass Index (BMI) than the H1N1 negative ICU admitted patients.
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Significant associations with outcomes variables, confounding, and effect modification were evaluated by stratified univariate analyses using exact categorical tests and the student's t test.
All the variables that were identified as significantly associated with event-free survival or maintenance of Child-Pugh class by univariate analyses were then examined using the Cox proportional hazards model to identify variables that were independently associated with event-free survival or maintenance of Child-Pugh class.
By univariate analyses with cognitive dysfunction, statin use, symptomatic status, apoE-ε4 status, preoperative monocyte counts, CRP, ICAM-1, and MMP-9 activity were indicated for inclusion in the final multivariate logistic regression model predicting cognitive dysfunction in type 2 diabetic CEA patients.
Prognostic factors were examined by univariate and multivariate analyses using the Cox proportional hazards model.
Prognostic factors were examined by univariate and multivariate analyses using a Cox proportional hazards model.
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by functional analyses using
by Western analyses using
by quantitative analyses using
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