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The variables were then re-examined in multivariate analysis (binary logistic regression) in order to identify the significant associations.
We performed a multivariate analysis (binary regression, stepwise procedure) to confirm the associations found previously in univariate analysis.
If this initial analysis demonstrates the need for multivariate analysis, binary logistic regression analysis will be used.
Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression).
The variables were also examined in the multivariate analysis (Binary logistic regression) in order to identify the significant predictors after controlling for other variables.
The variables were also examined using multivariate analysis (binary logistic regression) to assess the net effect of household headship on child death after controlling for the other variables.
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Subsequently we performed a multivariate analysis using binary regression (OR with 95% CI) and significant p < 0.05.
Potential variables were verified by multivariate analysis using binary logistic regression.
Bivariate and multivariate analysis with binary logistic regression to study the variables associated with frailty.
Further multivariate analysis by binary logistic regression was also achieved by SPSS.
#Multivariate analysis using binary logistic regression with a backwards step-wise approach.
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