线性回归模型的统计检验关系辨析

苎麻针织物在贴身穿着过程中产生较强的刺痒感,在一定程度上限制了苎麻织物的服用范围。为解决此问题,文章简要介绍了织物刺痒感的评价并针对如何改善甚至消除苎麻针织物刺痒感的问题进行了研究。首先通过单因素实验确定出各影响因素的范围,再通过正交试验并结合前臂实验法,利用评分的方式得出了一套最佳的酶处理工艺条件：pH值5、酶用量3%（owf）、浴比1∶20、温度45℃、时间45 min。     

Testing non-inferiority and superiority for two endpoints for several treatments with a control

Some multiple comparison procedures are described for multiple armed studies. The procedures are appropriate for testing all hypotheses for comparing two endpoints and multiple test arms to a single control group, for example three different fixed doses compared to a placebo. The procedure assumes that among the two endpoints, one is designated as a primary endpoint such that for a given treatment arm, no hypothesis for the secondary endpoint can be rejected unless the hypothesis for the primary endpoint was rejected. The procedures described control the family-wise error rate in the strong sense at a specified level α.     

A wide review on exponentiality tests and two competitive proposals with application on reliability

In this paper, two new statistics based on comparison of the theoretical and empirical distribution functions are proposed to test exponentiality. Critical values are determined by means of Monte Carlo simulations for various sample sizes and different significance levels. Through an extensive simulation study, 50 selected exponentiality tests are studied for a wide collection of alternative distributions. From the empirical power study, it is concluded that, firstly, one of our proposals is preferable for IFR (increasing failure rate) and UFR (unimodal failure rate) alternatives, whereas the other one is preferable for DFR (decreasing failure rate) and BFR (bathtub failure rate) alternatives and, secondly, the new tests can be considered serious and powerful competitors to other existing proposals, since they have the same (or higher) level of performance than the best tests in the statistical literature.     

An exhaustive numerical assessment of alternative unconditional tests of a binary treatment effect

For testing the effectiveness of a treatment on a binary outcome, a bewildering range of methods have been proposed. How similar are all these tests? What are their theoretical strengths and weaknesses? Which are to be recommended and what is a coherent basis for deciding? In this paper, we take seven standard but imperfect tests and apply three different methods of adjustment to ensure size control: maximization (M), restricted maximization (B) and bootstrap/estimation (E). Across a wide conditions, we compute exact size and power of the 7 basic and 21 adjusted tests. We devise two new measures of size bias and intrinsic power, and employ novel graphical tools to summarise a huge set of results. Amongst the 7 basic tests, Liebermeister’s test best controls size but can still be conservative. Amongst the adjusted tests, E-tests clearly have the best power and results are very stable across different conditions.     

A Potts‐mixture spatiotemporal joint model for combined magnetoencephalography and electroencephalography data

We develop a new methodology for determining the location and dynamics of brain activity from combined magnetoencephalography (MEG) and electroencephalography (EEG) data. The resulting inverse problem is ill‐posed and is one of the most difficult problems in neuroimaging data analysis. In our development we propose a solution that combines the data from three different modalities, magnetic resonance imaging (MRI), MEG and EEG, together. We propose a new Bayesian spatial finite mixture model that builds on the mesostate‐space model developed by Daunizeau & Friston [Daunizeau and Friston, NeuroImage 2007; 38, 67–81]. Our new model incorporates two major extensions: (i) We combine EEG and MEG data together and formulate a joint model for dealing with the two modalities simultaneously; (ii) we incorporate the Potts model to represent the spatial dependence in an allocation process that partitions the cortical surface into a small number of latent states termed mesostates. The cortical surface is obtained from MRI. We formulate the new spatiotemporal model and derive an efficient procedure for simultaneous point estimation and model selection based on the iterated conditional modes algorithm combined with local polynomial smoothing. The proposed method results in a novel estimator for the number of mixture components and is able to select active brain regions, which correspond to active variables in a high‐dimensional dynamic linear model. The methodology is investigated using synthetic data and simulation studies and then demonstrated on an application examining the neural response to the perception of scrambled faces. R software implementing the methodology along with several sample datasets are available at the following GitHub repository https://github.com/v2south/PottsMix . The Canadian Journal of Statistics 47: 688–711; 2019 © 2019 Statistical Society of Canada     

Democratic assessment as scales of justice: the case of three Iranian high-stakes tests

High-stakes tests are often used as instruments of agenda-setting and control in developing areas to enable policy-makers to establish and embed education policy agendas throughout the education system and society. As an alternative method, Critical Language Testing assumes that tests are value-laden instruments and products of political, social, cultural, and ideologically driven educational agendas. This article critically examines three Iranian high-stakes tests (the National University Entrance Exam, the MA/MS Exam, and PhD examinations) to evaluate whether covert policies and agendas are being deployed in the Iranian context. It applies qualitative methods and Strauss and Corbin’s [1998. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. London: Sage] constant comparative method to demonstrate the existence of clear patterns of domination. Democratic testing is therefore suggested as a way forward by which policy-makers can operationalize a just and fair exam whereby testing parties’ ideas, and intuitions are equally taken into account and their rights are protected.     

Computationally efficient familywise error rate control in genome-wide association studies using score tests for generalized linear models

In genetic association studies, detecting phenotype–genotype association is a primary goal. We assume that the relationship between the data—phenotype, genetic markers and environmental covariates—can be modeled by a generalized linear model. The number of markers is allowed to be far greater than the number of individuals of the study. A multivariate score statistic is used to test each marker for association with a phenotype. We assume that the test statistics asymptotically follow a multivariate normal distribution under the complete null hypothesis of no phenotype–genotype association. We present the familywise error rate order k approximation method to find a local significance level (alternatively, an adjusted p-value) for each test such that the familywise error rate is controlled. The special case k=1 gives the Šidák method. As a by-product, an effective number of independent tests can be defined. Furthermore, if environmental covariates and genetic markers are uncorrelated, or no environmental covariates are present, we show that covariances between score statistics depend on genetic markers alone. This not only leads to more efficient calculations but also to a local significance level that is determined only by the collection of markers used, independent of the phenotypes and environmental covariates of the experiment at hand.     

Partial Identification in Triangular Systems of Equations With Binary Dependent Variables

This paper studies the special case of the triangular system of equations in Vytlacil and Yildiz (2007), where both dependent variables are binary but without imposing the restrictive support condition required by Vytlacil and Yildiz (2007) for identification of the average structural function (ASF) and the average treatment effect (ATE). Under weak regularity conditions, we derive upper and lower bounds on the ASF and the ATE. We show further that the bounds on the ASF and ATE are sharp under some further regularity conditions and an additional restriction on the support of the covariates and the instrument.     

我国林产品对外贸易和经济发展的关系分析

运用格兰杰(Granger)因果检验法和联立方程组模型构建我国林产品对外贸易与经济发展关系的联立方程组模型,在样本区间内实证分析得出以下结论:(1)我国林产品出口与GDP之间具有正向相互促进作用,而林产品进口对GDP、林产品出口也均具有一定的正向促进作用;(2)林产品出口对GDP的贡献小于林产品进口对GDP的贡献。本研究为我国制订及实施科学合理的林产品贸易政策提供一个理论支撑。     

我国农村经济低水平均衡状态研究——基于金融约束视角的实证分析

以我国农村金融与农村经济相互制约形成的低水平均衡状态为研究对象,一方面从理论角度分析其形成机理,另一方面通过构建长期均衡的协整方程、进行Granger因果检验等实证方法,对二者的相互作用作进一步分析,并寻求破解农村金融约束的途径。