Sentence examples for multivariate stepwise multiple from inspiring English sources

Univariate and multivariate stepwise multiple logistic regression analysis was undertaken to assess predictors of CIN.

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 multivariate analysis, stepwise multiple linear regressions were first done to select the best subset of covariates among age, CAG repeat length, total testosterone, free testosterone and dihydrotestosterone.

Three clustering analyses (linear discriminant analysis, support vector machines, and random forest) and three multivariate regression methods (stepwise multiple linear regression, MLR; partial least squares regression, PLSR; and penalized spline) were used for pattern recognition and to develop the petroleum predictive models.

We secondly performed multivariate regression analysis and stepwise multiple linear regression analysis to determine independent relationships to the PON1 activity or MBF, including all variables with significant correlations on univariate analysis.

Spearman correlations and Kruskal Wallis tests were used to examine univariate relationships between variables; but for multivariate analysis parametric forward stepwise multiple regression was used, in the absence of a suitable non-parametric alternative.

The multivariate analysis involved a stepwise multiple linear regression model, using as dependent variables those resulting from the differences in evaluation of the target organ lesions between the two measures (Difference IMT = IMT2-IMT1, Difference PWV = PWV2-PWV1, Difference PDVCORNELL = PDVCORNELL2- PDVCORNELL1, and Difference ABI = ABI2-ABI1).

Multivariate analysis included both Forward Stepwise Multiple Logistic Regression Analysis and Forward Stepwise Multiple Linear Regression Analysis.

17 Multivariate analysis consisted of forward, stepwise multiple linear regression techniques to assess possible associations between depression (dependent variable) and CBI dimensions and sociodemographic characteristics as independent variables.

When analysis of several variables is needed, a multivariate analysis using the forward stepwise multiple regression method will be performed to construct models to explain the variability observed in the population and assess the combined effect of different variables.

To identify multivariate predictors of COMPASS total scores, stepwise multiple regression analysis was used.