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Factor loadings are the correlations between each variable and the factor.
Univariable analysis first assessed the association between each variable and ESBL-PE ICUAP.
The model coefficients' size indicated the strength of the relationship between each variable and the outcome variable.
Similar result is also confirmed by the structure matrix which shows the absolute correlation between each variable and any discriminant function.
Correlation analysis was also run in order to examine the magnitude and direction of relationship between each variable and the IFA indicator.
The Pearson correlation coefficients are used in analyzing the correlation degree between each variable, and the values of these correlation coefficients should be between − 1 and 1.
The odds ratios (OR) with 95% confidence interval (CI) for relationship between each variable and LN involvement (yes or no) were calculated using logistic regression.
These axes can be interpreted by considering the factor loadings of initial variables, which means squared correlation coefficient between each variable and each axis.
The main factors affecting the cost-effectiveness of the intervention were identified in the estimated model by calculating Spearman's rank correlation coefficients as a measure of the magnitude of the association between each variable and the ICERs.
The strength of the association between each variable and the outcome was assessed using the sub-hazard ratio, which is the ratio of hazards associated with the cumulative incidence function under different values of the covariates.
In all four birds beak gape is weighted heavier in the first discriminant function whereas OEC expansion is weighted more in the second, as shown by the standardized coefficients and the correlation between each variable and any discriminant function (Table 2).
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