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Conventional bivariate methods were used to compare participant groups.
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Both bivariate and multivariate analysis methods were used.
When joint estimation methods were used, bivariate probit/Tobit models were estimated.
Bivariate and multivariable logistic regression methods were used to estimate adjusted associations.
Bivariate random-effects meta-analytic methods were used to obtain pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR) and receiver operating characteristic (ROC) curves.
Because the variables were not normally distributed, a Spearman's rho bivariate correlational statistical method was used.
In the first the traditional approach is used, where a single material balance is formulated for the disperse phase along with PBM, while in the second a true bivariate/multivariate solution method is used.
Bivariate correlations were used for statistical analysis.
For this propose univariate and bivariate frequency distributions were used.
The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas.
Descriptive statistics, bivariate- (chi-square tests) and multivariate methods (linear regressions) were used to examine differences in population health.
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