Large Sample Tests Research Articles

Modelling size effect on rock aggregates strength using a DEM bonded-cell model

Empirical evidence has shown that particle breakage affects the mechanical behaviour of granular materials. The source of this mechanism takes place at the particle scale, and the main consequence on the macromechanical behaviour is increasing compressibility. Due to the inverse correlation between particle size and particle crushing strength, coarse rockfill materials are particularly vulnerable to mechanical degradation due to particle breakage. However, such coarse materials do not fit in standard laboratory devices, and the alternative of large sample testing is usually unavailable or too expensive. Alternatively, recent works have proposed multi-scale approaches using the discrete element method (DEM) to carry out numerical testing of coarse crushable materials, although few studies have focused on size effects. This article presents the application of a DEM bonded-cell model to study particle size-strength correlation on angular rock aggregates. Each particle is modelled by a cluster of perfectly rigid polyhedral cells with Mohr–Coulomb contact law. Constant cell density within particles implies that the presence of potential fragmentation planes increases with size. Therefore, particle strength decreases with size. A comprehensive sensitivity analysis was carried out through 1477 particle crushing simulations in a given particle size. Based on published experimental data on calcareous rock aggregates, part of the simulations were used for calibration, and 97 additional simulations of a coarser size fraction were performed for validation. The results show a good agreement with the empirical data in terms of size effect and data scatter through Weibull statistics.

Rapid Crack Detection Method of High-grade Cement Concrete Pavement

A new fast automatic repaired crack detection method of high-grade cement concrete pavement was realized through inhibition of groove, image enhancement, crack extraction and crack stitching in the low-resolution images using wavelet decomposition on the basis of in-depth feature analysis of repaired cracks. In addition, the modified crack identification algorithms were discussed in detail with joints, strip stains and traffic markings. It has significantly improved the processing speed by reducing image resolution and the applying one-dimensional convolution template instead of two-dimension. Large sample tests showed that recognition rate close to 94%.

Scale design of opinion leaders’ impact on online consumers’ purchasing intention

With the promotion of opinion leader’s impact on online purchase intention, the problem of how to measure the characteristics of opinion leader, the characteristics of opinion leader’s recommendation information and the influence of consumers’ characteristics on purchase intention is becoming more and more urgent. Based on numbers of popular scales, this paper designs the questionnaire items for the variables of professional knowledge, product involvement, visual cues, interactivity, functional value and trust involved in the opinion leader influence model, and forms the initial scale. On this basis, with the help of small-scale interviews, small sample pre-test and large sample test, trust and purchase intention fail to pass the validity test. Through correlation coefficient analysis, some questions with lower coefficient value are eliminated, and then the final scale with good reliability and validity is obtained.

Strategy-Structure Fit in the Shadow of Exploration-Exploitation

This study provides the first large-sample test of Chandler’s famous strategy-structure hypothesis in the context of the exploration-exploitation trade-off. To this end, we construct measures of the degree to which strategies and organizational structure are oriented towards exploration as opposed to exploitation for a representative panel dataset of all Canadian business firms. We obtain three main results. First, high intensity of exploration strategies is negatively related to high intensity of exploitation strategies, as implied by a strategic exploration-exploitation trade-off. Second, higher relative importance of exploration (exploitation) in strategy is systematically correlated with more adoption of organizational practices that support exploration (exploitation). We show that this pattern holds dynamically as well, as strategic repositioning towards exploration is systematically correlated with restructuring towards exploration-supporting practices. Additionally, this strategy-structure relationship continues to hold if we instrument strategic positioning using firm peers. Third, intensifying low-cost competition, which reduces the benefits of exploitation strategies leads to a systematic shift towards more exploration strategies, while increasing misalignment between strategy and structure.

Kurtosis test of modality for rotationally symmetric distributions on hyperspheres

A test of modality of rotationally symmetric distributions on hyperspheres is proposed. The test is based on a modified multivariate kurtosis defined for directional data on Sd. We first reveal a relationship between the multivariate kurtosis and the types of modality for Euclidean data. In particular, the kurtosis of a rotationally symmetric distribution with decreasing sectional density is greater than the kurtosis of the uniform distribution, while the kurtosis of that with increasing sectional density is less. For directional data, we show an asymptotic normality of the modified spherical kurtosis, based on which a large-sample test is proposed. The proposed test of modality is applied to the problem of preventing overfitting in non-geodesic dimension reduction of directional data. The proposed test is superior than existing options in terms of computation times, accuracy and preventing overfitting. This is highlighted by a simulation study and two real data examples.

Harmonic analysis and distribution-free inference for spherical distributions

Fourier analysis, and representation of circular distributions in terms of their Fourier coefficients, is quite commonly discussed and used for model-free inference such as testing uniformity and symmetry, in dealing with 2-dimensional directions. However, a similar discussion for spherical distributions, which are used to model 3-dimensional directional data, is not readily available in the literature in terms of their harmonics. This paper, in what we believe is the first such attempt, looks at probability distributions on a unit sphere through the perspective of spherical harmonics, analogous to the Fourier analysis for distributions on a unit circle. Representation of any continuous spherical density in terms of spherical harmonics is given, and such series expansions provided for some commonly used spherical distributions, as well as for two new spherical distributions that are introduced. Through the prism of harmonic analysis, one can look at the mean direction, dispersion, and various forms of symmetry for these models in a nonparametric setting. Aspects of distribution-free inference such as estimation and large-sample tests for various symmetries, are provided, each type of symmetry being characterized through its harmonics. The paper concludes with a real-data example analyzing the longitudinal sunspot activity.

Self-Concept in the Context of Diabetes Prevention: Development of the Lifestyle Health-Related Self-Concept Questionnaire

Understanding psychosocial factors in the context of lifestyle change is important to recognize distinctions in type 2 diabetes prevention behaviors. A relatively stable psychosocial feature, such as health-related self-concept (HRSC), may indicate factors that promote or repress positive health behaviors. The present study created a questionnaire specific to lifestyle change activities by modifying the Generalized Health-Related Self-Concept Questionnaire (G-HRSC). A modified lifestyle health-related self-concept (Lifestyle-HRSC) questionnaire was developed through creation of new items, context expert review of new items, and small and large sample test of new items. 101 college students completed the Lifestyle-HRSC. Kaiser-Meyer-Olkin (0.64) and Bartlett sphericity tests (χ2 = 6350.7 [ df = 3081], P < .01) indicated the sample met criteria for factor analysis. Principle component factor analysis was performed using varimax rotation with Kaiser normalization. Six factors were revealed: nutrition, social support, avoiding diabetes, physical activity, problem solving, and challenges related to being healthy. Item analysis was conducted to remove correlated and conceptually redundant items and to create the 31-item final questionnaire. The Lifestyle-HRSC provides additional knowledge regarding the relationship between self-concept and health as well as insights into the role of psychosocial factors in the context of diabetes prevention.

A flexible cure rate model based on the polylogarithm distribution

ABSTRACTModels for dealing with survival data in the presence of a cured fraction of individuals have attracted the attention of many researchers and practitioners in recent years. In this paper, we propose a cure rate model under the competing risks scenario. For the number of causes that can lead to the event of interest, we assume the polylogarithm distribution. The model is flexible in the sense it encompasses some well-known models, which can be tested using large sample test statistics applied to nested models. Maximum-likelihood estimation based on the EM algorithm and hypothesis testing are investigated. Results of simulation studies designed to gauge the performance of the estimation method and of two test statistics are reported. The methodology is applied in the analysis of a data set.

A large sample test for the length of memory of stationary symmetric stable random fields via nonsingular ℤd-actions

AbstractBased on the ratio of two block maxima, we propose a large sample test for the length of memory of a stationary symmetric α-stable discrete parameter random field. We show that the power function converges to 1 as the sample-size increases to ∞ under various classes of alternatives having longer memory in the sense of Samorodnitsky (2004). Ergodic theory of nonsingular ℤd-actions plays a very important role in the design and analysis of our large sample test.

Inferring the interaction structure of resistance to antimicrobials

The growth of antimicrobial resistance presents a significant threat to human and animal health. Of particular concern is multi-drug resistance, as this increases the chances an infection will be untreatable by any antibiotic. In order to understand multi-drug resistance, it is essential to understand the association between drug resistances. Pairwise associations characterize the connectivity between resistances and are useful in making decisions about courses of treatment, or the design of drug cocktails. Higher-order associations, interactions, which tie together groups of drugs can suggest commonalities in resistance mechanism and lead to their identification. To capture interactions, we apply log-linear models of contingency tables to analyze publically available data on the resistance of Escheresia coli isolated from chicken and turkey meat by the National Antimicrobial Resistance Monitoring System. Standard large sample and conditional exact testing approaches for assessing significance of parameters in these models breakdown due to structured patterns inherent to antimicrobial resistance. To address this, we adopt a Bayesian approach which reveals that E. coli resistance associations can be broken into two subnetworks. The first subnetwork is characterized by a hierarchy of β-lactams which is consistent across the chicken and turkey datasets. Tier one in this hierarchy is a near equivalency between amoxicillin-clavulanic acid, ceftriaxone and cefoxitin. Susceptibility to tier one then implies susceptibility to ceftiofur. The second subnetwork is characterized by more complex interactions between a variety of drug classes that vary between the chicken and turkey datasets.

Resampling-Based Inference Methods for Comparing Two Coefficients Alpha.

The two-sample problem for Cronbach's coefficient [Formula: see text], as an estimate of test or composite score reliability, has attracted little attention compared to the extensive treatment of the one-sample case. It is necessary to compare the reliability of a test for different subgroups, for different tests or the short and long forms of a test. In this paper, we study statistical procedures of comparing two coefficients [Formula: see text] and [Formula: see text]. The null hypothesis of interest is [Formula: see text], which we test against one-or two-sided alternatives. For this purpose, resampling-based permutation and bootstrap tests are proposed for two-group multivariate non-normal models under the general asymptotically distribution-free (ADF) setting. These statistical tests ensure a better control of the type-I error, in finite or very small sample sizes, when the state-of-affairs ADF large-sample test may fail to properly attain the nominal significance level. By proper choice of a studentized test statistic, the resampling tests are modified in order to be valid asymptotically even in non-exchangeable data frameworks. Moreover, extensions of this approach to other designs and reliability measures are discussed as well. Finally, the usefulness of the proposed resampling-based testing strategies is demonstrated in an extensive simulation study and illustrated by real data applications.

Experimental results of near real-time protection system for plasma facing components in Wendelstein 7-X at GLADIS

One of the aims of stellarator Wendelstein 7-X (W7-X), is to investigate steady state operation, for which power exhaust is an important issue. The predominant fraction of the energy lost from the confined plasma region will be absorbed by an island divertors, which is designed for steady state operation. In order to protect the divertor targets from overheating, 10 state-of-the-art infrared endoscopes will be installed at W7-X. In this work, we present the experimental results obtained at the high heat flux test facility GLADIS (Garching LArge DIvertor Sample test facility in IPP Garching) [] during tests of a new plasma facing components (PFCs) protection algorithm designed for W7-X. The GLADIS device is equipped with two ion beams that can generate a heat load in the range from 3 MWm−2 to 55 MWm−2. The algorithms developed at W7-X to detect defects and hot spots are based on the analysis of surface temperature evolution and are adapted to work in near real-time. The aim of this work was to test the near real-time algorithms in conditions close to those expected in W7-X. The experiments were performed on W7-X pre-series tiles to detect CFC/Cu delaminations. For detection of surface layers, carbon fiber composite (CFC) blocks from the divertor of the Wendelstein 7-AS stellarator were used to observe temporal behavior of fully developed surface layers. These layers of re-deposited materials, like carbon, boron, oxygen and iron, were formed during the W7-AS operation. A detailed analysis of the composition and their thermal response to high heat fluxes (HHF) are described in []. The experiments indicate that the automatic detection of critical events works according to W7-X PFC protection requirements.

Improved inference in dispersion models

• A Bartlett-type correction to the gradient statistic in dispersion models is derived. • The correction improves the chi-squared approximation when the sample size is finite. • A comprehensive simulation study compares several different tests in small samples. • Large sample tests, including the gradient test, may perform poorly in small samples. • Bartlett and Bartlett-type corrections remove size distortions with no power loss. We derive a general matrix Bartlett–type correction factor to the gradient statistic in the class of dispersion models. The correction improves the large–sample χ 2 approximation to the null distribution of the gradient statistic when the sample size is finite. We conduct Monte Carlo simulation experiments to evaluate and compare the performance of various different tests, namely the usual Wald, likelihood ratio, score, and gradient tests, the Bartlett–corrected versions of the likelihood ratio, score, and gradient tests, and bootstrap–based tests. The simulation results suggest that the analytical and computational corrections are effective in removing size distortions of the type I error probability with no power loss. The impact of the corrections in two real data applications is considered for illustrative purposes.

New two-sample tests for skewed populations and their connection to theoretical power of Bootstrap-t test

Various tests are available to compare the means of two populations. Tests for skewed data, however, are not well studied even though they are often needed in pharmaceutical study and agricultural economics. In particular, there is no available result to give power and sample size calculation for a two-sample Bootstrap-t test in skewed populations. In this paper, we propose easy-to-compute new tests and study their theoretical properties. The proposed work starts with derivation of a second-order Edgeworth expansion for the pooled two-sample t-statistic. Then new test rejection regions are formed based on Cornish–Fisher expansion of quantiles. The new tests account for first-order and second-order population skewnesses that were ignored in two-sample t test. We report the theoretical type I error accuracy and power of the newly proposed tests and the large sample t test. We also provide the detailed conditions under which the proposed tests give better power than the two-sample large sample test. Our new tests, \(\hbox {TCF}_1\) and TCF, are asymptotically equivalent to Bootstrap-t test up to \(O(N^{-1})\) and \(O(N^{-3/2})\), respectively. Compared with commonly used two-sample parametric and nonparametric tests, the new tests are computationally efficient, give better power for skewed data with moderate sample size, and provide sample size calculation to achieve desired power at a given significance level. Empirical studies confirmed our theoretical results.

A Relative Entropy Approach to Stochastic Dominance Analysis

This study formulates portfolio analysis in terms of Stochastic Dominance, Relative Entropy and Empirical Likelihood. We define a portfolio inefficiency measure based on the divergence between given probabilities and the nearest probabilities that rationalize a given portfolio for some admissible utility function. When applied to a sample of time-series observations in a blockwise fashion, the inefficiency measure becomes a Likelihood Ratio statistic for inequality moment conditions. The limiting distribution of the test statistic is bounded by a chi-squared distribution under general sampling schemes, allowing for conservative large-sample testing. We develop a tight numerical approximation for the test statistic based on a two-stage optimization procedure and piecewise linearization techniques. A Monte Carlo simulation study of the Empirical Likelihood Ratio test shows superior small-sample properties compared with various Generalized Method of Moments tests. An application analyzes the efficiency of a passive stock market index in data sets from the empirical asset pricing literature.

Merging data from multiple sources: pretest and shrinkage perspectives

ABSTRACTIn this article, we have developed asymptotic theory for the simultaneous estimation of the k means of arbitrary populations under the common mean hypothesis and further assuming that corresponding population variances are unknown and unequal. The unrestricted estimator, the Graybill-Deal-type restricted estimator, the preliminary test, and the Stein-type shrinkage estimators are suggested. A large sample test statistic is also proposed as a pretest for testing the common mean hypothesis. Under the sequence of local alternatives and squared error loss, we have compared the asymptotic properties of the estimators by means of asymptotic distributional quadratic bias and risk. Comprehensive Monte-Carlo simulation experiments were conducted to study the relative risk performance of the estimators with reference to the unrestricted estimator in finite samples. Two real-data examples are also furnished to illustrate the application of the suggested estimation strategies.

Compilation of the Elderly Functional Constipation Health Education Scale and its reliability and validity test

Objective To prepare the Elderly Functional Constipation(FC) Health Education Scale, and verify its reliability and validity. Methods The Elderly FC Health Education Scale was prepared by qualitative interviews, literature review, and Delphi method. The elderly patients who were over 60 years old and at Chinese PLA 181st Hospital were recruited by the purposive sampling method from January 2013 to August 2015.The diagnostic criteria of Roman Ⅲ was used to diagnose FC, the data of preliminary investigation and large sample test was used to form the formal scale, and its reliability and validity were further verified. Results The Elderly FC Health Education Scale was compiled with 6 dimensions and 28 items, and the Cronbach alpha coefficient which was the internal consistency reliability of the 6 factor was 0.965; the correlation coefficient analysis of equality reliability Kendall tau-b rank and various index variables score were positive correlation significantly. Both item level content validity index and scale level content validity index of the content validity were as a result of 1. The structure validity of the cumulated variance contribution ratio of the 6 factors were 60.15%. All factor loading coefficients between the items were more than 0.5, which indicated the fitting was good. Conclusions The reliability and validity of the Elderly FC Health Education Scale are good, and the scale may be used as a tool to prevent the elderly FC health education, and also be applied to the elderly FC patients in self-management and continue nursing after leaving hospital. Key words: Aged; Constipation; Scale; Reliability; Validity

Private placement and abnormal corporate payouts: evidence from large stock dividends

Dividends should be used as the way firms reward their investors, but in the Chinese stock market, large stock dividends have been criticised for several years. In this paper, through a case study and large-sample empirical tests, we find that large stock dividends are used to cater to investors participating in a firm’s private placement. Further empirical tests document that during the unlocking periods of privately issued new shares, firms are more likely to pay large stock dividends, especially when outside private placement investors are able to sell their shares. Additional tests reveal that private placement investors do make stock sales after receiving large stock dividends. Furthermore, firms undertaking large stock dividends after private placement have more frequent connected-party transactions, are more tunnelled by other receivables and have more aggressive earnings management and lower investment efficiencies, implying that the governance role of private placement is largely attenuated because of large stock dividends. Large stock dividends after private placement are also shown to be opportunistic behaviour and irrelevant to future performance in our study. Overall, the large stock dividends result in wealth transferring between insiders and ordinary investors, and further reduce the efficiency of resource allocation in the Chinese capital market. From the results we insist that regulators should encourage cash dividends and keep a close eye on potential abuse through large stock dividends.

Research on Statistics in Large Sample Test

Assuming that the test is one of the main contents of the statistical inference, it is widely used, and almost all of the major fields use hypothesis test, a statistical idea, and in the process of hypothesis testing, we need to construct a reasonable test statistic. Therefore, based on the hypothesis test and the knowledge of the central limit theorem, we construct a new test statistic when the sample size is sufficiently large, This statistic makes the calculation of the original test problem easier. This paper verifies the rationality of this test statistic by an example.

Improvement of the accuracy in testing the effect in the cox proportional hazards model using higher order approximations

Small-sample properties of the likelihood ratio test, the Wald test and the score test about significance of the effect in the Cox proportional hazards model for the right-censored and left-truncated data are investigated. These are large-sample tests, and, therefore, these are only approximate tests and they do not necessary maintain chosen significance level. Consequently, the p-value can be inaccurate as well. Higher order approximations of the likelihood function based on the Barndorff-Nielsen formula and the Lugannani-Rice formula are used in order to improve the accuracy of statistical inferences. The accuracy of these tests together with proposed approximations are compared by means of simulations under conditions of decreasing the sample size, and increasing proportion of right-censored and left-truncated data in the Cox model with the exponential and the Weibull distribution of the baseline hazard function. The results show that higher order approximations based on the Lugannani-Rice and the Barndorff-Nielsen formulas in combination with the Wald statistic improve the accuracy.