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In this work, we propose a method to build a structure function for a continuum system by using multivariate nonparametric regression techniques, in which certain analytical restrictions on the variable of interest must be taken into account.
Evolution of disease-severity scoring system TISS-28 (Therapeutic Intervention Scoring System) over the clinical course was evaluated by using multivariate nonparametric longitudinal data analysis in a two-factorial design (Brunner analysis).
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They can be reduced by using multivariate statistics.
By using multivariate -adic -integral on, one sees that (2.31).
Receiver operating characteristic curves were constructed by plotting sensitivity versus 1 − specificity obtained using multivariate logistic regression, and AUCs were compared using a nonparametric test (12).
Statistical analysis was performed by using univariate (nonparametric rank sum test) and multivariate (logistic regression) analysis to evaluate the relationship between gene expression and clinicopathological parameters, including age, FIGO stage, histological grade, lymph nodal involvement, residual tumor size, CA125, ER expression, PR expression and P53 expression.
Specifically, we used the multivariate nonparametric nearest neighbor imputation technique of [12], [13].
First, we obtain the nonparametric estimated calculation formula for expected utility by using the nonparametric estimation.
It was designed by using a nonparametric Bayesian approach.
The degree of association between nonparametric or ordinal variables was assessed by using Spearman nonparametric correlation.
Statistical significance was assessed by calculating 95% confidence intervals (CIs) and by using standard nonparametric statistics.
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