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Independent determinants were assessed by multivariable analyses using stepwise backward selection.
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This was followed by multivariable analyses used to assess the independent effect of each factor after controlling for other related factors.
Predictors of SNB positivity, RFS and OS were identified by univariable and multivariable analyses using STATA version 9 (StataCorp 2007, College Station, TX, USA).
Selected variables were further introduced in multivariable analyses using a hierarchical model with two random effects.
Multivariable analyses using the Cox proportional hazards model were used to estimate hazard ratios (HR) and test independent significance by backward elimination of insignificant explanatory variables.
Complex samples analysis option was used in statistical package for Social Sciences (SPSS) version 17. Univariate analyses followed by multivariable analyses were carried out.
Univariable and multivariable analyses were used to explore the relationships between antibiotic and homeopathic product use.
In multivariable analyses, we used 4 models.
Univariable and multivariable analyses were used to assess relations between baseline factors and the development of atrial fibrillation.
Linear and logistic multivariable analyses were used to obtain the risk-adjusted effect of BMI on these outcomes.
Multivariable analyses were used to identify variables predicting prognosis.
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