Comparison between a new computer program and the reference software for gray-scale median analysis of atherosclerotic carotid plaques
Ivan Benaduce CasellaRodrigo Bono FukushimaAnita Battistini de Azevedo MarquesMarcus Vinícius Martins CuryCalógero Presti
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Purpose To compare a new dedicated software program and Adobe Photoshop for gray-scale median (GSM) analysis of B-mode images of carotid plaques. Methods A series of 42 carotid plaques generating ≥50% diameter stenosis was evaluated by a single observer. The best segment for visualization of internal carotid artery plaque was identified on a single longitudinal view and images were recorded in JPEG format. Plaque analysis was performed by both programs. After normalization of image intensity (blood = 0, adventitial layer = 190), histograms were obtained after manual delineation of plaque. Results were compared with nonparametric Wilcoxon signed rank test and Kendall tau-b correlation analysis. Results GSM ranged from 00 to 100 with Adobe Photoshop and from 00 to 96 with IMTPC, with a high grade of similarity between image pairs, and a highly significant correlation (R = 0.94, p < .0001). Conclusions IMTPC software appears suitable for the GSM analysis of carotid plaques. © 2014 Wiley Periodicals, Inc. J Clin Ultrasound 43:194–198, 2015Rank (graph theory)
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The purpose of this study is to discuss the testing using the Mann-Whitney method and the Wilcoxon signaled level for learning perfect cube and cube root. This research is a quantitative study, while the method used is experimental. The quantitative approach used includes the Mann-Whitney test and Wilcoxon's signed rank test. The conclusions of this study are that: 1) for the Mann-Whitney test on the pretest value of the control group and the experimental group it is concluded that before the treatment of two groups, namely control and experiment, had the same ability in mastering the material to the third power and the cube root; 2) For the Mann-Whitney test on the post-test scores of the control group and the experimental group, it is concluded that after the treatment of two groups, namely the control and the experimental group, they have different abilities in mastery of the material in the third power and the cube root; whereas 3) for the Wilcoxon-signed level test on the pretest and posttest scores of the experimental group, it was concluded that there was a difference between the conditions before and after being given treatments on the mastery of the material to the third power and the perfect cube root.
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본 연구는 경로당 이용 여자노인에게 시행한 낙상예방운동이 체력에 미치는 효과를 확인하기 위해 시행하였다. 2019년 6월부터 12월까지 G시의 경로당 이용 노인 42명에게 낙상예방운동을 시행하였다. 대상자는 실험군과 대조군으로 나누었으며, 24주 동안 주당 3회 60분 동안 운동을 시행하였다. 실험 전과 후, 대상자들에게 체력을 평가하였다. 자료분석은 χ2 test, Fisher’s exact test, Wilcoxon rank sum test, Wilcoxon signed rank test, Mann Whitney U test를 시행하였다. 낙상예방운동 시행 후, 실험군이 대조군에 비해 의자에서 일어섰다 앉기, 덤벨들기, 의자에 앉아 앞으로 굽히기, 244㎝ 왕복 걷기가 유의하게 증가하였다. 반면, 2분 제자리 걷기, 등 뒤에서 양손잡기는 두 군간에 유의한 차이가 없었다. 낙상예방운동은 경로당에서 쉽게 모여 할 수 있는 방법이며, 가정에서도 개별적으로 대상자의 운동 강도를 조절하여 시행할 수 있는 운동이라고 생각한다.
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When the distributional assumptions for a t-test are not met, the default position of many analysts is to resort to a rank-based test, such as the Wilcoxon-Mann-Whitney Test to compare the difference in means between two samples. The Wilcoxon-Mann-Whitney Test presents no danger of tied observations when the observations in the data are continuous. However, in practice, observations are discretized due various logical reasons, or the data are ordinal in nature. When ranks are tied, most textbooks recommend using mid-ranks to replace the tied ranks, a practice that affects the distribution of the Wilcoxon-Mann-Whitney Test under the null hypothesis. Other methods for breaking ties have also been proposed. In this study, we examine four tie-breaking methods-average-scores, mid-ranks, jittering, and omission-for their effects on Type I and Type II error of the Wilcoxon-Mann-Whitney Test and the two-sample t-test for various combinations of sample sizes, underlying population distributions, and percentages of tied observations. We use the results to determine the maximum percentage of ties for which the power and size are seriously affected, and for which method of tie-breaking results in the best Type I and Type II error properties. Not surprisingly, the underlying population distribution of the data has less of an effect on the Wilcoxon-Mann-Whitney Test than on the t-test. Surprisingly, we find that the jittering and omission methods tend to hold Type I error at the nominal level, even for small sample sizes, with no substantial sacrifice in terms of Type II error. Furthermore, the t-test and the Wilcoxon-Mann-Whitney Test are equally effected by ties in terms of Type I and Type II error; therefore, we recommend omitting tied observations when they occur for both the two-sample t-test and the Wilcoxon-Mann-Whitney due to the bias in Type I error that is created when tied observations are left in the data, in the case of the t-test, or adjusted using mid-ranks or average-scores, in the case of the Wilcoxon-Mann-Whitney.
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This chapter looks at the equivalent of the t-test for non normally distributed data. The Mann–Whitney test is for unpaired data drawn from a population of observations in which the variable is not normally distributed. It assumes that there are two independent samples. It is the nonparametric equivalent of the unpaired t-test. The Wilcoxon signed-rank test is used for paired samples. It is the nonparametric equivalent of the paired t-test. The Wilcoxon Sign test is for paired samples where there is a binary outcome. The Wilcoxon sign test was most famously used in 1950s ads for washing powder. Statistical package for the social sciences (SPSS) provides useful and easy-to-interpret output for the nonparametric tests. The chapter presents the SPSS output for Mann–Whitney analysis, Wilcoxon sign test and Wilcoxon signed-rank test.
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There exist many misconceptions in choosing the t over the Wilcoxon Rank-Sum test when testing for shift. Examples are given in the following three groups: (1) false statement, (2) true premise, but false conclusion, and (3) true statement irrelevant in choosing between the t test and the Wilcoxon Rank Sum test.
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Background : In Indonesia ten percent of population will experience neck pain within one month. Almost every injury or disease in the neck will caused muscle spasms, pain of the neck pain can be reduced by using pharmacological and non-pharmacological therapy, non-pharmacological therapies that can be used is stretching exercises and hot compress therapy.
Benefit Research: To compare the two methods, hot compresses and stretching exercises.
Methods : Type of research is the study design Quasi-Experimental with pre and post test with two group design. This study took place in SMK N 1 Salatiga, Salatiga. Samples from this study as many as 12 people in the 2 treatment groups. Measurement of pain measured by VAS scale (Visual Analog Scale). The data obtained were then tested using the Wilcoxon Rank Sum Test, while for the effects of the two methods used Mann Whitney test.
Result : Analysis of the data in this study using a statistical test by Wilcoxon rank test in each group, from the first treatment group obtained P = 0.028 andtreatment group II obtained the value of P = 0,027 so that Ho is rejected, which means the treatment group I and II have a significant influence on the reduction of pain neck pain. Furthermore, the Mann Whitney test techniques to determine the value of the difference between the two treatment groups, in order to get the value of P = 0.127 which means that Ho is accepted that there is no difference in effect between group I and group II.
conclusion: The results showed that introducing a hot compress with and without the addition of stretching exercises may have a significant influence on the reduction of pain in the Neck Pain Syndrome. There is no significant effect between hot compresses with stretching exercises and without stretching addition to the reduce pain in the neck pain syndrome.
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Abstract The authors present an improved ranked set two‐sample Mann‐Whitney‐Wilcoxon test for a location shift between samples from two distributions F and G. They define a function that measures the amount of information provided by each observation from the two samples, given the actual joint ranking of all the units in a set. This information function is used as a guide for improving the Pitman efficacy of the Mann‐Whitney‐Wilcoxon test. When the underlying distributions are symmetric, observations at their mode(s) must be quantified in order to gain efficiency. Analogous results are provided for asymmetric distributions.
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The Mann-Whitney U test and the Wilcoxon signed-rank test are both commonly used two-sample nonparametric statistical tests. This chapter elaborates on the main principles for both tests. The Mann-Whitney U test and Wilcoxon signed-rank test are most applicable when the following assumptions are fulfilled: data type; distribution of data; sampling groups and observations; equal sample sizes; and random sampling. The Mann-Whitney U and the Wilcoxon signed-rank tests share similar hypotheses. In general, the hypotheses compare the median for population A to that of population B and evaluate differences between the populations. The null hypothesis (H0) states that the two samples come from the same population, indicating no difference. Statistical programs are used in the chapter to run a Mann-Whitney U and a Wilcoxon signed-rank test and determine the significance, or p-value, for a statistical analysis.
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ABSTRACT This paper presents a class of sub-sample rank-sum statistics to test the stochastic ordering between two distributions. The proposed class includes as special case the min–max test of Öztürk.[1] Öztürk, Ö. 2001. A Generalization of Ahmad's Class of Mann–Whitney–Wilcoxon Statistics. Austrl. and New Zealand J. Statist., 43: 67–74. [Crossref] , [Google Scholar] It is shown that the asymptotic distribution of the test statistic is normal and its Pitman asymptotic efficiency is as good as or higher than the competitors in the class of sub-sample Mann–Whitney–Wilcoxon statistics.
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