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Results by stepwise analysis were similar.
The results obtained by stepwise analysis were similar, except that LDL-C was associated with IHD in patients in the NP group.
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Multivariate logistic regression by backward stepwise analysis was performed to identify independent variables that correlated with the clinical outcome as of May 20 , 2003
Multivariate linear regression stepwise analysis was then performed by entering into model variables that were considered significant on univariate analysis to determine independent predictors of exercise capacity.
Variables with a p value <0.05 by univariate analysis were evaluated by stepwise logistic regression for inclusion in the final model.
All variables with p<0.1 by univariate analysis were evaluated by stepwise logistic regression for inclusion in the final logistic regression model.
Variables with p < 0.2 by univariate analysis were included in stepwise logistic regression models.
Variables, identified as significant by univariate analysis, were entered into stepwise multiple logistic regression (MLR) analysis and classification and regression tree (CRT) analysis to develop a decision algorithm for clinical application.
IC risk factors resulted significative by univariate analysis, were put in a stepwise logistic regression model.
In these cases, a significant difference was noted for DSP, but not distance shown in Table 2 and Table 3. Significant variables identified by univariate analysis were assessed in a stepwise multiple regression model, using backward elimination method.
The items significantly associated with CV by univariate analysis were then analysed by a stepwise multiple logistic regression.
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