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Results: A multivariate stepwise linear regression equation revealed that episiotomy adds nearly 3 cm to perineal lacerations.
In a multivariate stepwise linear regression model, change in sPLA2 correlated with change in hs-CRP (p <0.001), baseline LDL cholesterol level (p = 0.001), body mass index (p = 0.003), diabetes mellitus (p = 0.04) and combination therapy with ezetimibe/atorvastatin (p = 0.05).
Multivariate stepwise linear regression analysis was also performed to determine the factors associated with length of stay.
The multivariate stepwise linear regression analyses were performed with SPSS version 15.0 or R version 2.15.0 for Windows.
Second, even though we adjusted for traditional risk factors in the multivariate stepwise linear regression analysis, the possibility of residual confounding elements remains.
Multivariate stepwise linear regression analysis was conducted using the dependent variable, smad3, and those variables showing a significant correlation with smad3 as the independent variables.
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An univariate analysis followed by a multivariate stepwise linear-regression analysis, including all the collected variables, was also performed to predict the amikacin peak.
Considering log ZnT8A or log IA-2βA as dependent variables, parameters that came out with P < 0.1 in univariate analysis were further tested in a multivariate stepwise forward linear regression model.
We performed univariate [t-Test and analysis of variance (ANOVA)] and multivariate (stepwise multiple linear regression) analysis to evaluate eventual significant differences of mean PCS-12 and MCS-12 according to various characteristics (demographics, presence of chronic diseases, behavioral risk factors, and utilization of health services).
For the multivariate analysis, stepwise linear regression was performed.
At the multivariate analysis, stepwise linear regression was performed.
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