The Experts below are selected from a list of 106524 Experts worldwide ranked by ideXlab platform
Ronald H. Randles - One of the best experts on this subject based on the ideXlab platform.
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Power and sample size determinations for the Wilcoxon Signed-Rank Test
Journal of Statistical Computation and Simulation, 2007Co-Authors: Gwowen Shieh, Show Li Jan, Ronald H. RandlesAbstract:The problem of calculating power and sample size for the Wilcoxon Signed-Rank Test is discussed. The exact variance large-sample method is examined and explicit formulas are derived for observations from uniform, normal and Laplace distributions. Numerical results are presented to evaluate the exact variance procedure and compare its performance with two simplified approximations that have been suggested in the statistical literature. From the simulation results, it is evident that the exact variance approach is more accurate than the two approximate methods. To facilitate practical use, tabulated values of the estimated sample sizes are provided.
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Encyclopedia of Statistical Sciences - Multivariate Signed-Rank Tests†
Encyclopedia of Statistical Sciences, 2006Co-Authors: Ronald H. RandlesAbstract:A class of affine-invariant Signed Rank Test statistics is considered for the one-sample multivariate location problem. This class is obtained by modifying Randles’ sign Test which uses the transfo...
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Interdirection Tests for Simple Repeated-Measures Designs
Journal of the American Statistical Association, 1996Co-Authors: Show Li Jan, Ronald H. RandlesAbstract:Abstract Interdirection Tests are proposed for a simple repeated-measures design. The Test statistics proposed are applications of the one-sample interdirection sign Test and interdirection Signed-Rank Test to a repeated-measurement setting. The interdirection sign Test has a small-sample distribution-free property and includes the two-sided univariate sign Test and Blumen's bivariate sign Test as special cases. The interdirection Signed-Rank Test includes the two-sided univariate Wilcoxon Signed-Rank Test as a special case. The proposed statistics are shown to have a limiting X p−1 2 null distribution when the underlying distribution is elliptically symmetric. In addition, the asymptotic distributions of the proposed statistics under certain contiguous alternatives are obtained for elliptically symmetric distributions with a particular density function form. Pitman asymptotic relative efficiencies and Monte Carlo studies show the proposed interdirection Tests to be robust as compared to several competito...
Haixian Wang - One of the best experts on this subject based on the ideXlab platform.
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A novel index of functional connectivity: phase lag based on Wilcoxon Signed Rank Test
Cognitive Neurodynamics, 2020Co-Authors: Mengting Wei, Haixian Wang, Yiyun Guo, Hui FanAbstract:Phase synchronization has been an effective measurement of functional connectivity, detecting similar dynamics over time among distinct brain regions. However, traditional phase synchronization-based functional connectivity indices have been proved to have some drawbacks. For example, the phase locking value (PLV) index is sensitive to volume conduction, while the phase lag index (PLI) and the weighted phase lag index (wPLI) are easily affected by noise perturbations. In addition, thresholds need to be applied to these indices to obtain the binary adjacency matrix that determines the connections. However, the selection of the thresholds is generally arbitrary. To address these issues, in this paper we propose a novel index of functional connectivity, named the phase lag based on the Wilcoxon Signed-Rank Test (PLWT). Specifically, it characterizes the functional connectivity based on the phase lag with a weighting procedure to reduce the influence of volume conduction and noise. Besides, it automatically identifies the important connections without relying on thresholds, by taking advantage of the framework of the Wilcoxon Signed-Rank Test. The performance of the proposed PLWT index is evaluated on simulated electroencephalograph (EEG) datasets, as well as on two resting-state EEG datasets. The experimental results on the simulated EEG data show that the PLWT index is robust to volume conduction and noise. Furthermore, the brain functional networks derived by PLWT on the real EEG data exhibit a reasonable scale-free characteristic and high Test–reTest (TRT) reliability of graph measures. We believe that the proposed PLWT index provides a useful and reliable tool to identify the underlying neural interactions, while effectively diminishing the influence of volume conduction and noise.
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identifying intrinsic phase lag in eeg signals from the perspective of wilcoxon Signed Rank Test
International Conference on Neural Information Processing, 2017Co-Authors: John Q Gan, Haixian WangAbstract:In brain functional network connectivity analysis, phase synchronization has been effective in detecting regions demonstrating similar dynamics over time. The previously proposed connectivity indices such as phase locking value (PLV), phase lag index (PLI) and weighted phase lag index (WPLI) are widely used. They are, however, influenced by volume conduction or noise. In addition, appropriate thresholds have to be chosen in order to employ them successfully, which leads to uncertainty. In this paper, a novel connectivity index named phase lag based on the Wilcoxon Signed-Rank Test (PLWT) is proposed under the framework of Wilcoxon Signed-Rank Test, which avoids using thresholds to identify effective connections. We analyzed and compared PLWT with previous indices by simulating volume conduction and Testing the scale-free character of brain networks constructed based on EEG signals. The experimental results demonstrated that PLWT can be utilized as a reliable and convincing measure to reveal true connections while effectively diminishing the influence of volume conduction.
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ICONIP (3) - Identifying Intrinsic Phase Lag in EEG Signals from the Perspective of Wilcoxon Signed-Rank Test
Neural Information Processing, 2017Co-Authors: John Q Gan, Haixian WangAbstract:In brain functional network connectivity analysis, phase synchronization has been effective in detecting regions demonstrating similar dynamics over time. The previously proposed connectivity indices such as phase locking value (PLV), phase lag index (PLI) and weighted phase lag index (WPLI) are widely used. They are, however, influenced by volume conduction or noise. In addition, appropriate thresholds have to be chosen in order to employ them successfully, which leads to uncertainty. In this paper, a novel connectivity index named phase lag based on the Wilcoxon Signed-Rank Test (PLWT) is proposed under the framework of Wilcoxon Signed-Rank Test, which avoids using thresholds to identify effective connections. We analyzed and compared PLWT with previous indices by simulating volume conduction and Testing the scale-free character of brain networks constructed based on EEG signals. The experimental results demonstrated that PLWT can be utilized as a reliable and convincing measure to reveal true connections while effectively diminishing the influence of volume conduction.
Vance W Berger - One of the best experts on this subject based on the ideXlab platform.
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Wiley StatsRef: Statistics Reference Online - Randomized Block Design: Nonparametric Analyses†
Wiley StatsRef: Statistics Reference Online, 2014Co-Authors: Vance W BergerAbstract:In a randomized block design, there are, in addition to the experimental factor or factors of interest, one or more nuisance factors. The role of blocking is to reduce or eliminate that part of the experimental error attributable to these nuisance factors. Standard parametric ANOVA can be used to analyze such designs, but it requires the normality assumption, and may be misleading if the errors are not normally distributed or if there are outliers. In this article, we consider some distribution-free Tests, such as the sign Test, the Wilcoxon Signed Rank Test, Friedman's Test, aligned Rank Tests, Durbin's Test, and the row mean score Test. None of these methods require the normality assumption, and they can all be used to analyze such designs. Keywords: aligned Rank Test; balanced incomplete block design; Cochran–Mantel–Haenszel row mean score statistic; Durbin's Test; Friedman's Test; paired comparison design; randomized block design; randomized complete block design; sign Test; Wilcoxon Signed Rank Test
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Paired Observations, Distribution Free Methods†
Wiley StatsRef: Statistics Reference Online, 2014Co-Authors: Vance W BergerAbstract:Data are said to be paired if the ith observation on the first sample is naturally paired with the ith observation on the second sample. The objective in paired observations is to eliminate, to the extent possible, sources of extraneous variation. In behavioral studies, for example, paired observations may be employed to assess the effectiveness of a treatment or experimental procedure. Techniques often used to analyze paired observations include the McNemar Chi-square Test, the paired t Test, the sign Test, and the Wilcoxon Signed-Rank Test. Keywords: Mc Nemar Chi-square Test; paired observations; paired t Test; sign Test; Wilcoxon Signed-Rank Test
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randomized block design nonparametric analyses
Encyclopedia of Statistics in Behavioral Science, 2005Co-Authors: Vance W BergerAbstract:In a randomized block design, there are, in addition to the experimental factor or factors of interest, one or more nuisance factors. The role of blocking is to reduce or eliminate that part of the experimental error attributable to these nuisance factors. Standard parametric ANOVA can be used to analyze such designs, but it requires the normality assumption, and may be misleading if the errors are not normally distributed or if there are outliers. In this article, we consider some distribution-free Tests, such as the sign Test, the Wilcoxon Signed Rank Test, Friedman's Test, aligned Rank Tests, Durbin's Test, and the row mean score Test. None of these methods require the normality assumption, and they can all be used to analyze such designs. Keywords: aligned Rank Test; balanced incomplete block design; Cochran–Mantel–Haenszel row mean score statistic; Durbin's Test; Friedman's Test; paired comparison design; randomized block design; randomized complete block design; sign Test; Wilcoxon Signed Rank Test
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Encyclopedia of Statistics in Behavioral Science - Paired Observations, Distribution Free Methods
Encyclopedia of Statistics in Behavioral Science, 2005Co-Authors: Vance W BergerAbstract:Data are said to be paired if the ith observation on the first sample is naturally paired with the ith observation on the second sample. The objective in paired observations is to eliminate, to the extent possible, sources of extraneous variation. In behavioral studies, for example, paired observations may be employed to assess the effectiveness of a treatment or experimental procedure. Techniques often used to analyze paired observations include the McNemar Chi-square Test, the paired t Test, the sign Test, and the Wilcoxon Signed-Rank Test. Keywords: McNemar Chi-square Test; paired observations; paired t Test; sign Test; Wilcoxon Signed-Rank Test
Dave S. Kerby - One of the best experts on this subject based on the ideXlab platform.
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The Simple Difference Formula: An Approach to Teaching Nonparametric Correlation1:
Comprehensive Psychology, 2014Co-Authors: Dave S. KerbyAbstract:Abstract Although teaching effect sizes is important, many statistics texts omit the topic for the Mann-Whitney U Test and the Wilcoxon Signed-Rank Test. To address this omission, this paper introduces the simple difference formula. The formula states that the correlation equals the simple difference between the proportion of favorable and unfavorable evidence; in symbols this is r = f – u. For the Mann-Whitney U, the evidence consists of pairs. For the Signed-Rank Test, the evidence consists of Rank sums. Also, the formula applies to the Binomial Effect Size Display. The formula r = f – u means that a correlation r can yield a prediction so that the proportion correct is f and the proportion incorrect is u.
B. L. S. Prakasa Rao - One of the best experts on this subject based on the ideXlab platform.
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Wilcoxon-Signed Rank Test for associated sequences
Statistics & Probability Letters, 2005Co-Authors: Isha Dewan, B. L. S. Prakasa RaoAbstract:Let X1,...,Xn be stationary associated random variables with one dimensional marginal distribution function F. We study the properties of the classical sign statistic and the Wilcoxon-Signed Rank statistic for Testing for shift in location in the above set up. In the process, we extend the Newman's inequality to functions of bounded variation which are mixtures of absolutely continuous component and discrete component only.
