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BMI wasn't the significant independent predictor of PWV.> -wrap-foot> Mulinear linearegressionon analysis was arrived at using a backward, stepwise approach with probability of F = 0.05 for entry and 0.15 for removal from the model.
Then, multivariable, multilevel binomial logistic regression models were constructed with a manual backward stepwise approach, with a random intercept for hospital to account for clustering of observations from the same hospital and with a shrinkage factor to allow for inclusion of hospitals with small sample size.
In addition, we also performed multivariate survival analysis using Cox's regression model (with classic prognostic predictors entered in a backward stepwise approach with the log-likelihood ratio (L-R) significance test, using the default values for entering and exclusion criteria) to evaluate the independent prognostic value of the studied indices (SMI, MAI, and AI) in addition to MNA and FTD.
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Logistic regression analysis with a backward stepwise approach was employed to identify variables associated with TOD.
We developed Kaplan-Meier survival curves to compare outcomes and used multivariable Cox regression models to adjust for possible associations with morbidity and mortality, with a backward stepwise approach.
Table 3 demonstrates the result of the final logistic regression model with backward stepwise approach.
This analysis was modeled using multiple linear regression analysis with a backward, stepwise approach.
A backward stepwise approach was used to eliminate variables with p>0.10 to determine a final model.
Pulse wave velocity and augmentation index were modeled using multiple linear regression analysis with a backward, stepwise approach.
In each model we introduced age, gender, BMI, education, personal history of other disease into model and built the final model with a backward stepwise approach.
For multivariate analysis, variables with p values <0.25 were introduced into the model and removed after a backward stepwise approach, which resulted in only values with p<0.05 in the final model (except for age groups).
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