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The associations were further explored using multivariate logistic analysis.
The association of non-SLN or ⩾4 LN metastases with clinicopathological variables was investigated using multivariate logistic analysis.
We have analyzed eligible data using multivariate logistic analysis for 11 variables to reduce known confounding factors.
In addition, the risk factors for childhood drowning with socio-demographic, environmental and behavioural factors will be determined using multivariate logistic analysis.
Prevalence of malnutrition based on WHO/National Center for Health Statistics/Centers for Disease Control and Prevention z score ≤−2; weight for age, weight for height/length and height for age; proportions of underweight, wasting and stunting in cases and controls, and in acyanotic and cyanotic CHD; and predictors of malnutrition using multivariate logistic analysis.
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Variables that satisfied p-value < 0.2 were selected for further analysis using multivariate logistic regression analysis in order to control confounding effects.
In a second step, all statistically significant variables in the univariate analysis were tested using multivariate logistic regression analysis.
Individual AUCHD-MTX from population PK analysis was tested on drug toxicity and clinical outcome using multivariate logistic regression analysis and Cox hazards modelling.
Independent factors associated with SAE were identified using multivariate logistic regression analysis.
Predictive factors of WWLS were identified using multivariate logistic regression analysis.
Parameters associated with initial hyperlactatemia and lactate clearance were investigated using multivariate logistic regression analysis.
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