SIGNIFICANCE TEST FOR EMPIRICAL ORTHOGONAL FUNCTION (EOF) ANALYSIS OF METEOROLOGICAL AND OCEANIC DATA

A Monte Carlo experiment was done to create a statistically significant test table for selecting EOF modes whose signals are above the noise level. Numerical analysis showed that it is feasible to choose a shorter data set between temporal and spatial dimensions for conducting an EOF analysis, and thus simplify calculation of the covariance matrix and solution of its eigenvalues and eigenvectors. The experiment showed that the dominant EOF modes remained the same. This approach is more computationally efficient, reducing both computing time and computer memory requirement, while still retaining the dominant signal.

A SAS Macro for Testing Differences among Three or More Independent Groups Using Kruskal-Wallis and Nemenyi Tests

As a nonparametric method,the Kruskal-Wallis test is widely used to compare three or more independent groups when an ordinal or interval level of data is available,especially when the assump-tions of analysis of variance (ANOVA) are not met.If the Kruskal-Wallis statistic is statistically signifi-cant,Nemenyi test is an alternative method for further pairwise multiple comparisons to locate the source of significance.Unfortunately,most popular statistical packages do not integrate the Nemenyi test,which is not easy to be calculated by hand.We described the theory and applications of the Kruskal-Wallis and Nemenyi tests,and presented a flexible SAS macro to implement the two tests.The SAS macro was demonstrated by two examples from our cohort study in occupational epidemiology.It provides a useful tool for SAS users to test the differences among three or more independent groups using a nonparametric method.

Detecting the Relationship Between Summer Rainfall Anomalies in Eastern China and the SSTA in the Global Domain with a New Significance Test Method

It is suggested that the multiple samples in a correlation map or a set of correlation maps should be examined with significance tests as per the Bernoulli probability model. Therefore, both the contemporaneous and lag correlations of summertime precipitation R in any one of the three regions of Northern China （NC）, the Changjiang-Huaihe River Valley （CHRV）, and Southern China （SC） with the SSTA in the global domain have been tested in the present article, using our significance test method and the method proposed by Livezey and Chen （1983） respectively. Our results demonstrate that the contemporaneous correlations of sum- mer R in CHRV with the SSTA are larger than those in NC. Significant correlations of SSTA with CHRV R are found to be in some warm SST regions in the tropics, whereas those of SSTA with NC R, which are opposite in sign as compared to the SSTA-CHRVR correlations, are found to be in some regions where the mean SSTs are low. In comparison with the patterns of the contemporaneous correlations, the 1 to 12 month lag correlations between NC R and SSTA, and those between CHRV summer R and SSTA show similar patterns, including the magnitudes and signs, and the spatial distributions of the coefficients. However, the summer rainfall in SC is not well correlated with the SSTA, no matter how long the lag interval is. The results derived from the observations have set up a relationship frame connecting the precipitation anomalies in NC, CHRV, and SC with the SSTA in the global domain, which is critically useful for our understanding and predicting the climate variabilities in different parts of China. Both NC and CHRV summer R are connected with E1 Nifio events, showing a ‘- -＇pattern in an E1 Nifio year and a‘＋ ＋＇ pattern in the subsequent year. Key words summer precipitation; eastern China; global sea surface

An Intercomparison of Rules for Testing the Significance of Coupled Modes of Singular Value Decomposition Analysis

This paper clarifies the essence of the significance test of singular value decomposition analysis （SVD）, and investigates four rules for testing the significance of coupled modes of SVD, including parallel analysis, nonparametric bootstrap, random-phase test, and a new rule named modified parallel analysis. A numerical experiment is conducted to quantitatively compare the performance of the four rules in judging whether a coupled mode of SVD is significant as parameters such as the sample size, the number of grid points, and the signal-to-noise ratio vary. The results show that the four rules perform better with lower ratio of the number of grid points to sample size. Modified parallel analysis and nonparametric bootstrap perform best to abandon the spurious coupled modes, but the latter is better than the former to retain the significant coupled modes when the sample size is not much larger than the number of grid points. Parallel analysis and random-phase test are robust to abandon the spurious coupled modes only when either （1） the observations at the grid points are spatially uncorrelated, or （2） the coupled signal is very strong for parallel analysis and is not weak for random-phase test. The reasons affecting the accuracy of the test rules are discussed.

THE SIGNIFICANCE OF TESTING PREOPERATIVE VISUAL FUNCTION IN CATARACT USING LASER INTERFEROMETRIC VISUAL ACUITY AND ERG

Tests of preoperative visual function and prediction of postoperative E chart visual acuity(ECVA) using laser interferometric visual acuity(LIVA) and electroretinogram(ERG) were performed in 16 cases(19 eyes) of cataract. The results showed that the coincident rate between preoperative LIVA and postoperative ECVA was 63.2%, and there was a parallel correlation between preoperative amplitude of photopic ERG b-wave and postoperative ECVA in 79.0% of the eyes. Comparing these two methods, the test of LIVA ...

Improved significance testing of wavelet power spectrum near data boundaries as applied to polar research

When one applies the wavelet transform to analyze finite-length time series, discontinuities at the data boundaries will distort its wavelet power spectrum in some regions which are defined as a wavelength-dependent cone of influence （COI）. In the COI, significance tests are unreliable. At the same time, as many time series are short and noisy, the COI is a serious limitation in wavelet analysis of time series. In this paper, we will give a method to reduce boundary effects and discover significant frequencies in the COI. After that, we will apply our method to analyze Greenland winter temperature and Baltic sea ice. The new method makes use of line removal and odd extension of the time series. This causes the derivative of the series to be continuous （unlike the case for other padding methods）. This will give the most reasonable padding methodology if the time series being analyzed has red noise characteristics.

A New Method of Significance Testing for Correlation-Coefficient Fields and Its Application

Correlation-coefficient fields are widely used in short-term climate prediction research. The most frequently used significance test method for the correlation-coefficient field was proposed by Livezey, in which the number of significantcorrelation lattice(station) points on the correlation coherence map is used as the statistic. However, the method is based on two assumptions:(1) the spatial distribution of the lattice(station) points is uniform;and(2) there is no correlation between the physical quantities in the correlation-coefficient field. However, in reality, the above two assumptions are not valid.Therefore, we designed a more reasonable method for significance testing of the correlation-coefficient field. Specifically, a new statistic, the significant-correlation area, is introduced to eliminate the inhomogeneity of the grid(station)-point distribution, and an empirical Monte Carlo method is employed to eliminate the spatial correlation of the matrix.Subsequently, the new significance test was used for simultaneous correlation-coefficient fields between intensities of the atmospheric activity center in the Northern Hemisphere and temperature/precipitation in China. The results show that the new method is more reasonable than the Livezey method.

Significant Breakthrough in Industrial Test of the "Methanol to Olefins" Process Developed by Dalian Institute of Chemical Physics,Chinese Academy of Sciences

A process of ＂Methanol or Dimethylether to Olefins＂ developed by Dalian Institute of Chemical Physics （DICP）, designated as the DMTO process, has attained great success in industrial scaling up testing. DICP, by collaborating with the Xinxing Coal Chemical Co., Ltd. of Shaanxi Province and the Luoyang Petrochemical Engineering Co. of the SINOPEC Group, operated successfully a 50t（methanol）/d unit for the conversion of methanol to lower olefins, with a methanol conversion of close to 100%, and a selectivity to lower olefins（ethylene, propylene and butylenes） of higher than 90%. On 23rd August, the industrial test project has passed a state appraisal. The experts of the Appraisal Group, headed by Prof. YUAN Qingtang, academician of Chinese Academy of Engineering, drew the conclusions that the DMTO process, by utilizing a proprietary SAPO-34 catalyst system and a recycling fluidized bed reaction system for the production of lower olefins from methanol, is the first unit in the world having a capacity of producing nearly ten thousand tons lower olefins per year. The technological level of the industrial test is at a leading position internationally. This accomplishment will provide a sound base for the subsequent commercialization of the DMTO process.

High-risk symptoms and quantitative faecal immunochemical test accuracy: Systematic review and meta-analysis

BACKGROUND The quantitative faecal immunochemical test for haemoglobin(FIT) has been revealed to be highly accurate for colorectal cancer(CRC) detection not only in a screening setting, but also in the assessment of patients presenting lower bowel symptoms. Therefore, the National Institute for Health and Care Excellence has recommended the adoption of FIT in primary care to guide referral for suspected CRC in low-risk symptomatic patients using a 10 μg Hb/g faeces threshold.Nevertheless, it is unknown whether FIT′s accuracy remains stable throughout the broad spectrum of possible symptoms.AIM To perform a systematic review and meta-analysis to assess FIT accuracy for CRC detection in different clinical settings.METHODS A systematic literature search was performed using MEDLINE and EMBASE databases from inception to May 2018 to conduct a meta-analysis of prospective studies including symptomatic patients that evaluated the diagnostic accuracy of quantitative FIT for CRC detection. Studies were classified on the basis of brand,threshold of faecal haemoglobin concentration for a positive test result,percentage of reported symptoms(solely symptomatic, mixed cohorts) and CRC prevalence(< 2.5%, ≥ 2.5%) to limit heterogeneity and perform subgroup analysis to assess the influence of clinical spectrum on FIT′s accuracy to detect CRC.RESULTS Fifteen cohorts including 13073 patients(CRC prevalence 0.4% to 16.8%) were identified. Pooled estimates of sensitivity for studies using OC-Sensor at 10 μg Hb/g faeces threshold(n = 10400) was 89.6% [95% confidence interval(CI): 82.7%to 94.0%). However, pooled estimates of sensitivity for studies formed solely by symptomatic patients(n = 4035) and mixed cohorts(n = 6365) were 94.1%(95%CI: 90.0% to 96.6%) and 85.5%(95%CI: 76.5% to 91.4%) respectively(P <0.01), while there were no statistically significant differences between pooled sensitivity of studies with CRC prevalence < 2.5%(84.9%, 95%CI: 73.4% to 92.0%)and ≥ 2.5%(91.7%, 95%CI: 83.3% to 96.1%)(P = 0.25). At the same threshold, OCSensor? sensitivity to rule out any significant colonic lesion was 78.6%(95%CI:75.6% to 81.4%). We found substantial heterogeneity especially when assessing specificity.CONCLUSION The results of this meta-analysis confirm that, regardless of CRC prevalence,quantitative FIT is highly sensitive for CRC detection. However, FIT ability to rule out CRC is higher in studies solely including symptomatic patients.

The Regions with the Most Significant Temperature Trends During the Last Century

Having analyzed a global grid temperature anomaly data set and some sea level pressure data during the last century, we found the following facts. Firstly, the annual temperature change with a warming trend of about 0.6°C/ 100 years in the tropical area over Indian to the western Pacific Oceans was most closely correlated to the global mean change. Therefore, the temperature change in this area might serve as an indi-cator of global mean change at annual and longer time scales. Secondly, a cooling of about -0.3°C/ 100 years occurred over the northern Atlantic. Thirdly, a two-wave pattern of temperature change, warming over northern Asia and northwestern America and cooling over the northern Atlantic and the northern Pa-cific, occurred during the last half century linked to strengthening westerlies over the northern Atlantic and the weakening Siberian High. Fourthly, a remarkable seasonal difference occurred over the Eurasian con-tinent, with cooling (warming) in winter (summer) during 1896–1945, and warming (cooling) in winter (summer) during 1946-1995. The corresponding variations of the North Atlantic Oscillation and the South-ern Oscillation were also discussed. Key words Temperature trend - Mann-Kendall’s Test - Significance - Regional difference - Correlation coefficient This study was supported by the Ministry of Science and Technology Projects G1999043400 and Na-tional Key Project- “Studies on Short-Term Climate Prediction System in China” under Grant No.96-908-01-04.

Effect of Ascorbic Acid Supplementation on Liver Function Tests in Hepatitis C Patients

An isolated liver function test is of little role in selection of liver disease because many harmful liver diseases may be correlated with normal levels of LFT’s. The outline of enzyme abnormalities in the perspective of patient’s commonly observed symptoms and laboratory data might be helpful in directing the subsequent diagnosis of liver diseases. Liver Function Tests (LFTs) are most generally used screening blood tests for assessment of different liver diseases and these tests provide a lot of evidence for disease processes whether for the purpose of investigation of supposed liver disease or help in observing the progress of disease action or simply by blood investigation. The evaluation of different liver enzymes simply gives diagnostic information on basic level whether patient’s principal disorder is actually hepatitis or cholestasis in source. However, it is necessary in various cases to evaluate LFTs with knowledge of liver functioning enzyme fractions. The objective of this study was to explore the effects of ascorbic acid supplementation on serum liver function tests in Hepatitis C patients. A total of 100 hepatitis C patients were selected randomly. 50 were given ascorbic acid supplementation for one month along with anti HCV treatment. The other 50 HCV patients took their normal anti HCV treatment without intake of ascorbic acid supplementation, and serum ascorbic acid level and liver function test parameters were observed before and after intake of ascorbic acid in both groups. The liver function parameters determined were aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), serum total bilirubin, direct bilirubin, indirect bilirubin and serum protein (total protein, albumin, globulin and A/G ratio). These parameters along with serum ascorbic acid were measured before and 30 days after vitamin C supplementation. Various abnormally elevated LFTs were also improved more rapidly when compared to other group which was not given ascorbic acid supplements for the period of one month. There was a significant change in levels of some liver function parameters before and after intake of ascorbic acid supplementation, and various abnormally elevated LFTs were also improved when compared to other group which was not given ascorbic acid supplements for the period of one month. The effect of Vitamin C supplementation was more marked on serum aminotransferase levels. After one-month use of ascorbic acid, serum alanine aminotransferase (p < 0.042) and serum aspartate aminotransferase (p < 0.000) levels were significantly decreased in hepatitis C patient group. In HCV group with ascorbic acid supplementation, serum total bilirubin (p < 0.046) and serum direct bilirubin (p < 0.048) were found to be less than the pre values when compared to HCV group without ascorbic acid supplementation. It was also observed that some of protein values were suggestively improved after intake of ascorbic acid supplementation.

Detection of Clinically Significant Warm Reactive Anti-A1 in a Post Red Blood Cells Transfusion Patient with Acute Lymphoblastic Leukemia

The purpose of this article is to report that some anti-A1 that react at 37°C are IgG antibodies and are clinically significant, as they can cause the destruction of a proportion of A1 cells in vivo following the transfusion of red blood cells. Therefore, when a serum of an individual contains anti-A1, further testing of the plasma against group A1, A2, and O by referencing red blood cells and individual cells against anti-A1 lectin (Dolichos biflorus lectin) must be performed. Confirming the specificity of anti-A1 by referencing red blood cells is also important in selecting the appropriate blood for transfusion. ABO antibodies are naturally occurring and activate the complement cascade, making them more likely to cause severe transfusion reactions compared to antibodies to other RBC antigens.

一类变系数空间滞后的混合地理加权回归模型

为解决因变量空间滞后存在的局域性问题,对现有常系数空间滞后的混合地理加权回归模型作了具有更广泛形式的拓展,提出一类变系数空间滞后的混合地理加权回归(MGWR-VSLR)模型。MGWR-VSLR模型实现了空间相关性与空间异质性融合,涵盖了绝大多数地理加权回归的模型形式,基于重构参数化方法和似然比检验分别给出模型的系数估计方法与显著性检验以及选取变系数的判别检验。在蒙特卡罗模拟与实际应用中,MGWR-VSLR模型均表现出优异的因变量拟合与预测能力。MGWR-VSLR模型的提出为定量化研究空间效应问题设定适宜的模型形式提供了支撑依据。

基于Excel软件利用矩阵运算模拟多元线性回归模型的应用分析

文章基于多元线性回归分析的基本原理,模拟多元线性回归方程的矩阵,研究专业基础课程与专业核心课程的相关性.利用Excel软件中的矩阵函数的运算,对兰州城市学院财务管理专业110名学生的线性代数、概率论与数理统计和财务管理学课程卷面成绩为样本数据进行正态性分析.结果表明,课程成绩服从正态分布,据此建立卷面成绩的多元线性回归预测模型,通过对数据样本的方差分析和对统计量进行检验和统计推断,表明方程拟合度较好,以此帮助师生预测财务管理学课程成绩,针对三门课程预测的线性关系,对教师提出了一些教学建议.

基于离差平方和分解式的线性回归检验统计量的构建

文章基于样本数据离差平方和分解式,分析影响变量之间相关关系的因素.将离差平方和分解成回归平方和与残差平方和两部分,呈现出数据变异的根源在于变量自身取值的差异性和存在不可控制的随机因素两方面叠加的结果.建立线性回归数学模型,应用最小二乘估计法先求出回归方程参数的估计值,由估计值的数学期望、方差的性质,得到回归平方和、残差平方和服从正态分布、χ2分布的结论,再依据F分布、t分布的结构模式,构造回归分析显著性检验的F统计量、t统计量.文章理清了从离差平方和分解式、回归分析模型到选择检验统计量的思维线索.

起重违规作业致因及其影响路径分析

违规作业是起重机械事故高发的重要原因,基于人机交互仿真实验,探究影响起重机械违规作业的因素,并深入分析各因素对违规作业的影响路径。首先收集13项潜在起重违规作业影响因素,并进行295次人机实验,记录不同影响下的违规操作次数;之后基于方差分析、非参数检验、回归分析等方法筛选出具有显著影响的疲劳程度、工作难度和性别3项因素;最后基于文献回顾,对该3项影响因素分别建立中介模型和有调节的中介模型,从而分析其对违规操作的路径影响机制。结果表明:疲劳程度在性别与违规操作次数之间存在中介作用,为部分中介;疲劳程度在性别与违规操作次数之间存在中介作用的情况下,工作难度对中介的调节效应显著,为正向调节。

粗差和系统误差显著性检验统计量统一推导新方法

基于均值平移模型的数据探测法和附加系统参数的平差法是目前处理粗差和系统误差的重要方法,其函数模型形式一致,故关于二者的显著性检验统计量理论上可做统一推导。不同于已有文献,文中提出一种统一推导的新方法。新方法的思路更符合数理统计中构造显著性检验统计量的一般思路,具有简洁且易于理解的特点。此外,新方法还具有较强的普适性,除参数平差外,需要时还可用于其他平差方法的粗差与系统误差显著性检验统计量推导。

P值之争与管理学研究:先验概率的意义

P值之争的本质是人们把统计检验和统计推断混淆,直接用统计检验结果来进行统计推断.这导致许多似是而非的理论被接受.统计检验犯错的是假阳性概率.统计推断犯错的是假阳性之反概率.两种概率之间的数值关系受先验概率影响很大.先验概率越高,利用统计检验的结果进行推断所犯错误概率就越小.如果先验概率很小,即使假阳性概率很小,利用该结果进行推断所犯错误概率也很大.本文以管理学研究为例,提出解决该问题的办法是,通过与现实和与理论的双重对话来掌握先验概率,以提高基于统计检验的结果进行统计推断的可靠性.本文的科学哲学意义是,揭示了科学研究是先验与经验相统一的本质,以及科学研究的不充分决定性的特征.

面向乡村振兴的认养农业发展影响因素——基于咸阳市周边橙种植户的调查

为推进城郊认养农业发展,促进乡村进一步振兴,采用Logistic回归方法,从个人因素、家庭因素、生产因素和环境因素等4个维度对咸阳市周边橙种植户参与认养农业的意愿及影响因素进行研究。结果表明,咸阳周边农户参与认养农业意愿最强烈的影响因素为农户性别、文化程度、是否村干部或合作社成员、是否参与过认养农业、家庭耕地面积、农产品价格波动与滞销情况,均在1%水平上呈现正向显著相关;农户年龄、人口数量、收入来源是否为农业种植、生产对象的需求弹性等因素在5%水平上正向显著相关;家庭收入、市场规模、政策支持、自然灾害和交通便利程度等因素未通过显著性检验。基于实证结果和结合咸阳城郊认养农业发展实际,提出提高农户对认养农业的认知水平,鼓励农户进行规模化、标准化生产,建立专项补贴贷款渠道等措施,从而更好的促进咸阳城郊认养农业发展,加快乡村振兴。

基于Voronoi图的空间点事件统计聚类方法

挖掘地理空间数据中点事件聚集模式对于揭示流行疾病、犯罪分布热点区域及城市基础设施空间分布格局等具有重要意义。针对不同形状、密度和大小的显著空间点聚集模式的识别,目前以空间扫描统计为代表的方法虽然可以对空间点聚类的显著性进行统计推断,减少虚假聚类结果,但其主要用于识别球形或椭圆形状的聚簇,对于沿着街道或河道分布的任意形状、不同密度的显著空间点聚簇识别还存在局限。因此,本研究提出一种基于Voronoi图的空间点聚集模式统计挖掘方法。首先,采用Voronoi图来度量空间点分布的聚集性,将空间点聚类问题转化为热点区域探测问题;其次,结合局部Gi*统计量探测统计上显著的空间点聚簇;最后,通过模拟数据和真实犯罪事件数据进行实验与对比分析。结果表明:本方法能够有效探测任意形状的空间点聚类,并对空间点簇的显著性进行统计判别,识别显著的空间点簇,减少随机噪声点的干扰;聚类识别结果优于现有代表性方法,如DBSCAN算法、空间扫描统计方法等。