Statistical analysis of a two-unit dependent repairable system

Maximum likelihood estimators are investigated a for lr-out-of 2:G repairable system when failures and repairs are statistically dependent. Under two censoring schemes Accelerated Life Testing Procedure (ALTP) is used to obtain the estimates. Information matrices are supplied and a special case when the failure and repair phenomenon are independent of each other is considered.     

How to Teach by the Unit Method

Using data from the National Center for Educational Statistics research spanning fifteen years, researchers examined the impact of national educational policy implementation on the role of social studies in elementary schools. Specifically, with the reauthorization of No Child Left Behind (NCLB) in 2007 and the continuation of federal-mandated testing of English language arts (ELA) and mathematics in grades three through five, researchers sought to understand how policy decisions to extend testing to science affected teacher decisions in regard to instructional time allocations for core subject areas of ELA, mathematics, science, and social studies in elementary schools. Results of this quantitative study offer large-scale evidence of the declining role of social studies in an era in which testing is clearly linked to subject-area importance. Findings provide an overview of the national scope of testing and the ramifications for social studies in elementary schools. Researchers conclude that curriculum standardization, accountability, and high-stakes testing have had adverse affects on social studies time allotments in comparison to tested subjects.     

Conducting research using web-based questionnaires: Practical,methodological, and ethical considerations

The use of the internet for social science research is becoming increasingly common. This paper outlines practical, methodological and ethical issues for researchers to consider when using web-based questionnaires. This is illustrated by consideration of the authors' own experience of conducting a study into the phenomenon of self-harm.     

Stochastic comparisons of order statistics,with applications in relibility

This paper reviews recent developments in the stochastic comparison of order statistics. The results discussed are basically: (l) Stochastic comparisons of linear combinations of order statistics from distributions F and G where G^?1 F is convex or starshaped. (2) Stochastic comparisons of individual order statistics and of vectors of order statistics from underlying heterogeneous distributions by the use of majorization and Schur function theory. (3) Stochastic comparison of random processes. Applications to reliability problems are presented illustrating the use and value of the theoretical results described     

Bayes Analysis and Comparison of Accelerated Weibull and Accelerated Birnbaum–Saunders Models

Several models are proposed in the literature for modeling fatigue data resulting from materials subject to cyclic stress and strain. Accelerated Weibull and accelerated Birnbaum–Saunders distributions are most commonly used models. Whereas the accelerated Weibull model is easier compared to accelerated Birnbaum–Saunders, it fails to represent the situation equally well. The present article focuses on Bayes analysis of the two models and provides a comparison based on some important Bayesian tools. Model compatibility study using predictive simulation ideas is preceded by the said comparison. Throughout, the posterior simulations are carried out by Markov chain Monte Carlo procedure.     

Nonparametric Methods in Continuous Time Model Specification

Some popular parametric diffusion processes have been assumed as such underlying diffusion processes. This paper considers an important case where both the drift and volatility functions of the underlying diffusion process are unknown functions of the underlying process, and then proposes using two novel testing procedures for the parametric specification of both the drift and diffusion functions. The finite-sample properties of the proposed tests are assessed through using data generated from four popular parametric models. In our implementation, we suggest using a simulated critical value for each case in addition to the use of an asymptotic critical value. Our detailed studies show that there is little size distortion when using a simulated critical value while the proposed tests have some size distortions when using an asymptotic critical value in each case.     

语言测试研究的新视角：批判语言测试

长期以来，语言测试工作者研究的核心是如何提高测试的信度与效度，以客观、精确地测量考生的语言能力。语言测试尤其是大规模高风险语言测试带来的社会影响，很难由改良测试本身来解决。批判语言测试 (Critical Language Testing) 的提出把语言测试置于更广阔的社会政治语境中，对测试后效 (consequences) 的反思不再局限于反拨效应 (washback)，而是重新审视测试中渗透的权力与控制，测试所具有的社会价值、政治功能等。     

Non-linear models 1

This is the first application of a new method for testing stationary random point processes. Consider the class of all stationary ergodic point processes on the real line with arbitrary dependences among the inter–point distances (spacing).The hypothesis is :The observed process φ is a homogeneous Poisson process or more (resp.less) regular than a Poisson process.The sample is the vector of the first n points t₁, …,t_n.There is a close relation between our method for testing and queueing theory: For finding an appropriate test statistic, we observe the behaviour of a single server queue with the input φ.A table of critical values is given.     

Out-of-Sample Forecast Tests Robust to the Choice of Window Size

This article proposes new methodologies for evaluating economic models’ out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The study shows that the tests proposed in the literature may lack the power to detect predictive ability and might be subject to data snooping across different window sizes if used repeatedly. An empirical application shows the usefulness of the methodologies for evaluating exchange rate models’ forecasting ability.     

Bayesian goodness-of-fit test for censored data

We propose a Bayesian computation and inference method for the Pearson-type chi-squared goodness-of-fit test with right-censored survival data. Our test statistic is derived from the classical Pearson chi-squared test using the differences between the observed and expected counts in the partitioned bins. In the Bayesian paradigm, we generate posterior samples of the model parameter using the Markov chain Monte Carlo procedure. By replacing the maximum likelihood estimator in the quadratic form with a random observation from the posterior distribution of the model parameter, we can easily construct a chi-squared test statistic. The degrees of freedom of the test equal the number of bins and thus is independent of the dimensionality of the underlying parameter vector. The test statistic recovers the conventional Pearson-type chi-squared structure. Moreover, the proposed algorithm circumvents the burden of evaluating the Fisher information matrix, its inverse and the rank of the variance–covariance matrix. We examine the proposed model diagnostic method using simulation studies and illustrate it with a real data set from a prostate cancer study.