MAXIMUM TEST FOR A SEQUENCE OF QUADRATIC FORM STATISTICS ABOUT SCORE TEST IN LOGISTIC REGRESSION MODEL

This article proposes the maximum test for a sequence of quadratic form statistics about score test in logistic regression model which can be applied to genetic and medicine fields.Theoretical properties about the maximum test are derived.Extensive simulation studies are conducted to testify powers robustness of the maximum test compared to other two existed test.We also apply the maximum test to a real dataset about multiple gene variables association analysis.

A Gene Score Test for Disease Association with Multiple Genes

The traditional method for creating a gene score to predict a given outcome is to use the most statistically significant single nucleotide polymorphisms (SNPs) from all SNPs which were tested. There are several disadvantages of this approach such as excluding SNPs that do not have strong single effects when tested on their own but do have strong joint effects when tested together with other SNPs. The interpretation of results from the traditional gene score may lack biological insight since the functional unit of interest is often the gene, not the single SNP. In this paper we present a new gene scoring method, which overcomes these problems as it generates a gene score for each gene, and the total gene score for all the genes available. First, we calculate a gene score for each gene and second, we test the association between this gene score and the outcome of interest (i.e. trait). Only the gene scores which are significantly associated with the outcome after multiple testing correction for the number of gene tests (not SNPs) are considered in the total gene score calculation. This method controls false positive results caused by multiple tests within genes and between genes separately, and has the advantage of identifying multi-locus genetic effects, compared with the Bonferroni correction, false discovery rate (FDR), and permutation tests for all SNPs. Another main feature of this method is that we select the SNPs, which have different effects within a gene by using adjustment in multiple regressions and then combine the information from the selected SNPs within a gene to create a gene score. A simulation study has been conducted to evaluate finite sample performance of the proposed method.

Analysis of College Students’ Test Scores Based on Two-Component Mixed Generalized Normal Distribution

In order to improve the fitting accuracy of college students’ test scores, this paper proposes two-component mixed generalized normal distribution, uses maximum likelihood estimation method and Expectation Conditional Maxinnization (ECM) algorithm to estimate parameters and conduct numerical simulation, and performs fitting analysis on the test scores of Linear Algebra and Advanced Mathematics of F University. The empirical results show that the two-component mixed generalized normal distribution is better than the commonly used two-component mixed normal distribution in fitting college students’ test data, and has good application value.

Score Tests for Zero-inflated Double Poisson Regression Models

Count data with excess zeros encountered in many applications often exhibit extra variation. There- fore, zero-inflated Poisson （ZIP） model may fail to fit such data. In this paper, a zero-inflated double Poisson model （ZIDP）, which is generalization of the ZIP model, is studied and the score tests for the significance of dis- persion and zero-inflation in ZIDP model are developed. Meanwhile, this work also develops homogeneous tests for dispersion and/or zero-inflation parameter, and corresponding score test statistics are obtained. One numer- ical example is given to illustrate our methodology and the properties of score test statistics are investigated through Monte Carlo simulations.

OUTLIER SCORE TEST IN A GROWTH CURVE MODEL

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Assessment of cardiovascular risk in diabetes:Risk scores and provocative testing

Cardiovascular disease(CVD) is the leading cause of morbidity and mortality among patients with diabetes mellitus,who have a risk of cardiovascular mortality two to four times that of people without diabetes.An individualised approach to cardiovascular risk estimation and management is needed.Over the past decades,many risk scores have been developed to predict CVD.However,few have been externally validated in a diabetic population and limited studies have examined the impact of applying a prediction model in clinical practice.Currently,guidelines are focused on testing for CVD in symptomatic patients.Atypical symptoms or silent ischemia are more common in the diabetic population,and with additional markers of vascular disease such as erectile dysfunction and autonomic neuropathy,these guidelines can be difficult to interpret.We propose an algorithm incorporating cardiovascular risk scores in combination with typical and atypical signs and symptoms to alert clinicians to consider further investigation with provocative testing.The modalities for investigation of CVD are discussed.

基于Dynaform的汽车后风窗罩板成形工艺参数优化研究

文中以某汽车后风窗罩板为研究对象,解决其成形过程中的破裂和回弹缺陷。首先,运用Dynaform软件构建了符合实际工况的仿真模型;然后,选择对成形质量影响较大的模具间隙、摩擦因数、压边力和冲压速度作为主要因素,设计了4因素4水平的正交试验方案,并进行了仿真分析;接着,以最大减薄率和回弹作为评价指标进行综合评分,并采用Minitab软件对综合评分进行均值分析,获得了影响成形质量的各因素的主次关系和最优冲压工艺参数组合:摩擦因数为0.085,冲压速度为5000 mm/s,压边力为65 kN,模具间隙为1.15 mm;最后,选用上述工艺参数进行仿真分析和生产验证,产品拉延区域未出现破裂的成形缺陷,左右两端的弧形位置未见明显回弹。

医学类本科生、硕士研究生医学统计学学习态度及其与考试成绩的关系

目的调查某医科大学医学类本科生、硕士研究生医学统计学学习态度现状,探索影响因素,分析其与考试成绩的关系,为提高医学统计学教学质量提供思路和依据。方法以内蒙古某医科大学2021年秋季学期开设医学统计学课程的本科生和硕士研究生为调查对象,调查并分析学生基本信息和医学统计学学习态度。结果多重线性回归分析显示,性别、学历与学生医学统计学学习态度无关;数学能力越强、学习时长越长,医学统计学学习态度越积极。相关性分析显示,学习时长与医学统计学考试成绩呈正相关关系。结论学生医学统计学学习态度不太积极,存在畏难情绪。数学能力、学习时长对医学统计学学习态度产生影响,学习积极性与考试成绩呈正相关关系;不同学历学生的学习时长均与考试成绩呈正相关关系。建议针对不同学历的学生开展针对性教学,在提高学习积极性的同时,利用多元化教学方式,不断进行统计学技能训练,加深学生对医学统计学知识的理解。

Multiple z-Score Based Method for Noninvasive Prenatal Test Using Cell-Free DNA in Maternal Plasma

Objective: To improve the detecting accuracy of chromosomal aneuploidy of fetus by non-invasive prenatal testing (NIPT) using next generation sequencing data of pregnant women’s cell-free DNA. Methods: We proposed the multi-Z method which uses 21 z-scores for each autosomal chromosome to detect aneuploidy of the chromosome, while the conventional NIPT method uses only one z-score. To do this, mapped read numbers of a certain chromosome were normalized by those of the other 21 chromosomes. Average and standard deviation (SD), which are used for calculating z-score of each sample, were obtained with normalized values between all autosomal chromosomes of control samples. In this way, multiple z-scores can be calculated for 21 autosomal chromosomes except oneself. Results: Multi-Z method showed 100% sensitivity and specificity for 187 samples sequenced to 3 M reads while the conventional NIPT method showed 95.1% specificity. Similarly, for 216 samples sequenced to 1 M reads, Multi-Z method showed 100% sensitivity and 95.6% specificity and the conventional NIPT method showed a result of 75.1% specificity. Conclusion: Multi-Z method showed higher accuracy and robust results than the conventional method even at low coverage reads.

基于不同神经网络模型预测体测成绩

为更加准确地反应当前学生的身体素质情况,基于多个不同的神经网络模型构建体测成绩预测模型,为降低体测成绩中各项目数据之间的相关性,使用主成分分析法对数据集进行处理。使用BP神经网络结合脉冲神经网络构建一个预测模型,加强模型处理分析数据集的能力,提高预测的准确性。在长短期记忆神经网络中加入注意力机制构建另一个预测模型,使模型更加关注数据集中的关键信息。通过实验,预测模型输出的预测值与实际值的重合率高达90%以上,预测准确率整体在95%以上。

测试集有效性评价:问题、进展与挑战

测试用例集的缺陷检测有效性指测试集能够在多大程度上检测出软件中存在的缺陷.如何评价测试集的缺陷检测有效性是一个重要问题.覆盖率和变异得分是两个最重要和最广泛使用的测试集有效性度量.为量化测试集的缺陷检测能力,研究人员对测试集有效性评价进行了大量研究并且取得了较大的进展.与此同时,现有研究存在不一致的结论,该领域依然存在一些亟待解决的挑战.对多年来国内外学者在测试集有效性评价领域的研究成果进行系统性的梳理和总结.首先,阐述测试集有效性评价研究中的问题.然后,介绍并分析基于覆盖率和基于变异得分的测试集有效性的评价以及介绍测试集有效性评价在测试集优化中的应用.最后,指出测试集有效性评价研究中面临的挑战并给出建议的研究方向.

加权非线性随机系数模型异方差性的Score检验

在回归分析中 ,随机误差的方差齐性的假设往往有助于问题的解决 ,但方差齐性假设并不总是正确的。在线性和非线性回归中关于异方差的诊断问题已有许多讨论。在韦博成 (1995 )讨论的加权非线性回归模型的基础上 ,用随机系数的方法 ,讨论加权线性随机系数模型中的异方差检验问题 ,得到了方差齐性检验的Score统计量。

具有线性趋势回归信度模型的随机效应及线性趋势的Score检验

讨论了具有线性趋势的回归信度模型的随机效应和线性趋势的Score检验问题.首先分别推导出模型中随机效应存在性和线性趋势显著性这2种检验的Score检验统计量,然后利用Monte-Carlo方法分别模拟了此2种检验统计量的功效.功效模拟结果显示,2种检验统计量都有很好的检验效果.最后利用所得到的检验方法对旅客意外身体伤害保险数据进行了实例分析,分析结果表明,该数据集的随机效应是存在的,线性趋势也是显著的.

一般均值漂移模型的Score检验统计量

本文研究了一般均值漂移模型中漂移量的存在性检验问题.利用Score函数和Fisher信息阵,获得了检验的Score统计量.

零截尾广义Poisson回归模型及其Score检验(英文)

研究零截尾广义Poisson回归模型,给出了模型的参数估计方法,着重研究检验零截尾Poison回归、零截尾广义Poisson回归以及检验回归系数显著性的score检验统计量,并用一个数值实例来说明方法的有效性.最后通过一个仿真模拟例子来研究score检验统计量的检验功效.

基于重复测量数据的Poisson回归模型的偏大离差的Score检验

Poisson回归模型广泛应用于分析计数型数据 ,Dean&Lawless(1989)和Dean(1992 )讨论了非重复测量得到的计数型数据的偏大离差存在性的检验问题 .本文分别利用随机系数模型和对数非线性模型讨论了基于重复测量得到的计数型数据的偏大离差的检验问题 ,得到了检验的score统计量 .

区域选取对图像信息法可预测性的影响

图像信息(PI)法是一种基于统计物理学的地震预测方法,因其对中长期地震预测有较好的效果已在国内外广泛应用。PI方法在计算过程中对选取区域的所有网格参量进行了归一化,因此不同的区域选取会产生PI热点结果的变化。本文基于中国地震台网中心自1970年以来的全国M_(S)≥3.0地震目录,采用5年尺度的“异常学习时段”和“预测时间窗”以及1年尺度的滑动时间步长,以南北地震带2016年以来发生的M_(S)≥6.0地震的回溯性预测检验为例,研究了不同空间范围的选取对PI方法地震预测效能的影响。地震预测效能检验采用R值评分法和受试者工作特征(ROC)检验方法。结果显示:①在其它计算参数相同的情况下,不同的区域选取对PI预测结果有较大影响;②利用R值评分和ROC检验方法对不同研究区的预测效能进行评估时,区域内部地震活动性差异小的区域预测效果较好,而对于地震活动性存在较大差异的区域,地震活动性高的区域内发生的地震更容易被预测,推测导致这一结果的可能原因是地震活动性较强的区域出现的异常更显著,而算法里的归一化过程会抑制地震活动性较低区域出现的异常,从而造成漏报;③对于具体的目标地震,震中附近的PI热点图像会经历演化,因此利用PI方法向前预测时要结合多个时间窗口进行综合预测;④不同于其它天然构造地震的热点演化趋势,2019年四川长宁M_(S)6.0地震和2021年四川泸县M_(S)6.0地震震中附近热点反复出现、消失,可能与人工活动有关;⑤滇西南地区、海原断裂中东部附近、小江断裂中部地区、龙门山断裂南部和小江断裂东北部地区存在持续出现的PI热点,这些区域为值得关注的M_(S)≥6.0地震发震区域。

TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS

In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).

正交试验法优选熏洗舒筋汤的制备工艺

[目的]优选熏洗舒筋汤的提取工艺。[方法]以浸泡时间、乙醇体积分数、乙醇用量为考察因素,新乌头碱、次乌头碱为评价指标,采用L9(34)正交试验设计,根据综合评分优选提取工艺。[结果]熏洗舒筋汤最优提取工艺为:按熏洗舒筋汤处方比例称取生川乌、生草乌粗粉1份量,加入2倍量的80%乙醇浸泡12 h,装入渗漉筒中再加入10倍量的80%乙醇渗漉。收集渗漉液,减压回收乙醇至液体无醇味。再将生川乌、生草乌的药渣与艾叶、宽筋藤、苏木、红花、两面针、海桐皮、爬山虎、透骨草等八味药水煮提取2次,第一次1.5 h,第二次1 h,过滤,弃去残渣,滤液浓缩,放凉,与渗漉液合并混匀。将樟脑研磨成细粉,与酒精按1∶10的比例溶解加入浓缩的药液中,加水定容至1 000 ml,即得。[结论]优选的熏洗舒筋汤工艺稳定可行,可为进一步的工业生产提供依据。