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In addition, association between different variables with mortality was sought.
Degree of bivariate associations was measured using the Pearson Chi Square test to assess the significance between different variables, with significance level set at p < 0.05.
Degree of bivariate association was measured by using the Pearson Chi square test to assess the significance between different variables, with a significance level set at p = 0.05.
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Pearson correlation coefficients with Bonferroni correction were calculated to examine the relationship between different variables related with the hippocampal neuroplasticity and the behavioral measures.
The Z test and chi square test was used to observe the difference between different variables and strength of the relationship with logistic regression.
Multivariate analysis was performed using multiple logistic regression (Enter method) to assess the independent adjusted relationship between different variables and CHD with independent variables being those with P ≤ 0.05 in univariate logistic regression analysis.
The relationship between different variables was tested with linear regression analysis.
The statistical significance of no association between different variables was performed with the Fisher' s exact test.
Frequencies and the association between different variables (chi-square test with Yate's correction and Fisher's exact test) were analyzed using the SPSS software (version 11.5).
Two different statistical analyses were performed to test the: 1) association between the different variables with the four lung scoring systems, and 2) association among the four different lung scoring methods used.
Correlations between different variables in patients were assessed with the Spearman rank correlation test.
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