## What is/are Parametric Comparison?

Parametric Comparison - It can also improve nonparametric comparison of preferences as suggested by Heufer (2014).^{[1]}Appropriate nonparametric comparisons were made to evaluate differences across time, between limbs, and between groups.

^{[2]}Nonparametric comparisons were made.

^{[3]}Pairwise, nonparametric comparisons and multivariate analyses were used to evaluate the relationships between the three imaging parameters (FF, |G*|, and G″) and histologic features.

^{[4]}We developed an algorithm where centiles were allocated using non-parametric comparison to controls, generating multiparameter heat maps to simultaneously represent all leukocyte subpopulations for inspection of trends within a cohort or segregation with a putative genetic mutation.

^{[5]}Non-parametric comparison was used, and a p value of <0.

^{[6]}Wilcoxon Rank Sums tests were used for nonparametric comparison of dosimetric data between patients with and without RP; p-values were Bonferroni adjusted when applicable.

^{[7]}Using a non-parametric comparison of the AUCs, there was no statistical significance between each of the scores for both symptomatic and asymptomatic populations (P=0.

^{[8]}Nonparametric comparisons were performed using Wilcoxon signed rank test.

^{[9]}In global non-parametric comparisons FDR-corrected for multiple comparisons, CSF levels of 5 cytokines (FGF-2, IL-10, MCP-3, IL-12p40, MDC) differed among the three groups.

^{[10]}The non-parametric comparison of different sociodemographic groups showed no differences between genders and almost no differences among the age groups.

^{[11]}Non-parametric comparisons of means showed no significant differences in mean respiratory rates or NQ scores between patients with and without Ilo.

^{[12]}This paper deals with a parametric comparison of the differences between American and Australian codes (ASCE-7 16 and AS1170.

^{[13]}Nonparametric comparison (Wilcoxon-Mann-Whitney and Kruskal-Wallis) and correlation(Spearman) tests were used to evaluate associations of demographic data, clinical parameters, and depression, anxiety, social support, HAQ-DI scores with ULS-8 score.

^{[14]}Parametric comparison of ultra-compact few-mode waveguides of three types (strip, rib, and buried) on thin-film Lithium Niobate On Insulator (LNOI) and SOI platforms is presented.

^{[15]}Based on non-parametric comparisons of the generated MOE, we found that aggregating course evaluation data from two courses reduced the MOE in most cases.

^{[16]}This paper aims to discuss an insight of these approaches and to highlight the parametric comparison.

^{[17]}The primary analysis was a receiver operating characteristics curve, (ROC curve) for the blood glucose diagnostic for predicting hypotension outcome with 95% confidence for the area under the curve and non-parametric comparison to 0.

^{[18]}Based on these results, a parametric comparison is carried out to quantitatively describe the impact of recirculation process on the effectiveness of other parameters.

^{[19]}Thus, according to their health status and socio-demographics, seafarers were classified and their impact on job satisfaction and burnout were examined by nonparametric comparison of multivariate samples analysis.

^{[20]}The horizontal line profile and other parametric comparisons indicate that the proposed method can suppress beam-hardening artifacts significantly.

^{[21]}Nonparametric comparison in the groups with the Mann– Whitney test showed a statistically significant (p = 0.

^{[22]}This distribution allows the use of these variables in parametric comparisons.

^{[23]}The Shapiro-Wilk test was utilized to assess the normality of the distribution and non-parametric comparisons were performed.

^{[24]}Parametric comparison and results of training and testing proved that Support Vector Machine (SVM) performed very well.

^{[25]}A parametric comparison between the conventional MPA and superstrateloaded MPA has been carried out.

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## Exhaustive Parametric Comparison

Subsequently, an exhaustive parametric comparison from the existing pre-trained model has been established to validate the improved efficacy and productivity.^{[1]}Moreover, the exhaustive parametric comparison of the variant with the classical network and the pre-trained network is presented.

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## parametric comparison test

Variables were compared using the Kruskal-Wallis test, and Dunn's nonparametric comparison test was performed for post-hoc analysis to determine differences between clusters.^{[1]}Results were analyzed using parametric comparison tests with significance value 0.

^{[2]}After classifying the patients into two groups according to pathological N stage, the optimal threshold values of all metabolic parameters were compared between groups using a non-parametric comparison test.

^{[3]}Non-parametric comparison tests were performed to determine intervention effect and compare subgroups.

^{[4]}For the parameters investigated (autocorrelation and outlier range), a detection rate was generated in each chart, and nonparametric comparison tests were applied.

^{[5]}Data were analyzed using parametric and nonparametric comparison tests and multivariable regression to control for confounders.

^{[6]}A statistical analysis suitable for mixed type distributions was conducted: for the discrete component a logistic regression model was used and for the continuous component the impact of the variables on MBL was examined by using robust nonparametric comparison tests.

^{[7]}Multi-level regression analyses and non-parametric comparison tests were applied to the data from 60 soybean farms, 30 of each production system.

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## parametric comparison study

Additionally, although subsequent parametric comparison studies on the transient performance of both systems revealed similar effect on system performance subject to same geometrical/operational parameter variation, the analyses also further confirm solid prevalence of the CO2 system over that of R-134a, in terms of COP, SMER and drying time.^{[1]}We present a parametric comparison study for three types of CFD models (2D axisymmetric, Semi-3D and 3D) in which we study the impact of model reduction on three models on the predicted FFR.

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## parametric comparison method

The Parametric Comparison Method synthesises phylogenetic methods developed in evolutionary biology with the generative conception of binary syntactic parameters to generate phylogenetic trees for languages based on their parameter settings.^{[1]}In the case of normally distributed data, parametric comparison methods were used, while if all or one of the compared groups deviated from normality, non-parametric methods were used.

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