Parametric Comparison(参数比较)研究综述
Parametric Comparison 参数比较 - 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. [26]正如 Heufer (2014) 所建议的，它还可以改善偏好的非参数比较。 [1] 进行了适当的非参数比较以评估跨时间、肢体之间和组之间的差异。 [2] 进行了非参数比较。 [3] 成对、非参数比较和多变量分析用于评估三个成像参数（FF、|G*| 和 G″）与组织学特征之间的关系。 [4] 我们开发了一种算法，其中使用与对照的非参数比较来分配百分位数，生成多参数热图以同时表示所有白细胞亚群，以检查队列内的趋势或具有推定基因突变的分离。 [5] 使用非参数比较，p值<0。 [6] 使用 Wilcoxon 秩和检验对有和没有 RP 患者之间的剂量学数据进行非参数比较； p 值在适用时进行了 Bonferroni 调整。 [7] 使用 AUC 的非参数比较，有症状和无症状人群的每个分数之间没有统计学意义（P = 0. [8] 使用 Wilcoxon 符号秩检验进行非参数比较。 [9] 在针对多重比较进行 FDR 校正的全局非参数比较中，5 种细胞因子（FGF-2、IL-10、MCP-3、IL-12p40、MDC）的 CSF 水平在三组之间存在差异。 [10] 不同社会人口学组的非参数比较显示，性别之间没有差异，年龄组之间几乎没有差异。 [11] 平均值的非参数比较显示，有和没有 Ilo 的患者的平均呼吸频率或 NQ 评分没有显着差异。 [12] 本文处理美国和澳大利亚代码（ASCE-7 16 和 AS1170. [13] 非参数比较（Wilcoxon-Mann-Whitney 和 Kruskal-Wallis）和相关性（Spearman）检验用于评估人口统计数据、临床参数和抑郁、焦虑、社会支持、HAQ-DI 评分与 ULS-8 评分之间的关联。 [14] 介绍了薄膜绝缘体上铌酸锂 (LNOI) 和 SOI 平台上三种类型（条形、肋形和埋入式）的超紧凑少模波导的参数比较。 [15] 基于生成的 MOE 的非参数比较，我们发现在大多数情况下，汇总来自两门课程的课程评估数据会降低 MOE。 [16] 本文旨在讨论这些方法的见解并强调参数比较。 [17] 主要分析是用于预测低血压结果的血糖诊断的受试者工作特征曲线（ROC 曲线），曲线下面积的置信度为 95%，非参数比较为 0。 [18] 基于这些结果，进行了参数比较，以定量描述再循环过程对其他参数有效性的影响。 [19] 因此，根据他们的健康状况和社会人口统计，海员被分类，并通过多变量样本分析的非参数比较来检查他们对工作满意度和倦怠的影响。 [20] 水平线轮廓和其他参数比较表明，所提出的方法可以显着抑制光束硬化伪影。 [21] 使用 Mann-Whitney 检验的组中的非参数比较显示有统计学意义（p = 0. [22] 这种分布允许在参数比较中使用这些变量。 [23] Shapiro-Wilk 检验用于评估分布的正态性，并进行了非参数比较。 [24] 参数比较以及训练和测试结果证明支持向量机（SVM）表现非常好。 [25] 对传统 MPA 和超载 MPA 进行了参数比较。 [26]
Exhaustive Parametric Comparison 详尽的参数比较
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. [2]随后，已经建立了与现有预训练模型的详尽参数比较，以验证改进的功效和生产力。 [1] 此外，还给出了该变体与经典网络和预训练网络的详尽参数比较。 [2]
parametric comparison test 参数比较测试
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. [8]使用 Kruskal-Wallis 检验比较变量，并使用 Dunn 的非参数比较检验进行事后分析以确定集群之间的差异。 [1] 使用显着性值为 0 的参数比较检验分析结果。 [2] 将患者按病理N分期分为两组后，采用非参数比较检验比较各组代谢参数的最佳阈值。 [3] 进行非参数比较测试以确定干预效果并比较亚组。 [4] 对于研究的参数（自相关和离群值范围），在每个图表中生成检测率，并应用非参数比较测试。 [5] 使用参数和非参数比较测试和多变量回归分析数据以控制混杂因素。 [6] 进行了适用于混合类型分布的统计分析：对于离散分量，使用逻辑回归模型，对于连续分量，通过使用稳健的非参数比较测试检查变量对 MBL 的影响。 [7] 对来自 60 个大豆农场、每个生产系统 30 个的数据进行了多层次回归分析和非参数比较检验。 [8]
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. [2]此外，尽管随后对两个系统的瞬态性能的参数比较研究揭示了在相同的几何/操作参数变化下对系统性能的相似影响，但分析还进一步证实了 CO2 系统相对于 R-134a 系统的稳固流行，就以下方面而言COP、SMER 和干燥时间。 [1] 我们对三种类型的 CFD 模型（2D 轴对称、半 3D 和 3D）进行了参数比较研究，其中我们研究了模型缩减对三种模型对预测 FFR 的影响。 [2]
parametric comparison method 参数比较法
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. [2]参数比较方法综合了进化生物学中开发的系统发育方法与二元句法参数的生成概念，以根据其参数设置为语言生成系统发育树。 [1] 在正态分布数据的情况下，使用参数比较方法，而如果所有或一个比较组偏离正态性，则使用非参数方法。 [2]