Inference for quantile measures of kurtosis,peakedness, and tail weight

Insight into measures of peakedness, heavy-tailedness, and kurtosis can be gained by studying Ruppert’s ratios of interquantile ranges. They are not only monotone in Horn’s measure of peakedness when applied to the central portion of the population, but also monotone in the practical tail-index of Morgenthaler and Tukey, when applied to the tails. Non-parametric confidence intervals are found for Ruppert’s ratios, and sample sizes required to obtain such intervals for a pre-specified relative width and level are provided. In addition, the empirical power of distribution-free tests for peakedness and bimodality are found for some symmetric distributions.     

Optimal and lead-in adaptive allocation for binary outcomes: A comparison of Bayesian methods

We compare posterior and predictive estimators and probabilities in response-adaptive randomization designs for two- and three-group clinical trials with binary outcomes. Adaptation based upon posterior estimates are discussed, as are two predictive probability algorithms: one using the traditional definition, the other using a skeptical distribution. Optimal and natural lead-in designs are covered. Simulation studies show that efficacy comparisons lead to more adaptation than center comparisons, though at some power loss, skeptically predictive efficacy comparisons and natural lead-in approaches lead to less adaptation but offer reduced allocation variability. Though nuanced, these results help clarify the power-adaptation trade-off in adaptive randomization.     

Examining implementation and preliminary performance indicators of veterans treatment courts: The Kentucky experience

Veterans’ Treatment Courts (VTCs) are posited as a solution to offer rehabilitation for veterans involved in the criminal justice system. Despite the pervasive implementation of VTCs, there is little research focused specifically on VTC implementation and outcomes, which are based on other problem-solving court models such as drug court. The current study presents qualitative process evaluation data from key stakeholders (n = 21) and veteran participants (n = 4) to show accomplishments, challenges, and lessons learned during first-year implementation at two VTC sites. Quantitative performance data is also presented on veteran participants (n = 19) served during the first year to show: types of services, monitoring, judicial interaction, sanctions/therapeutic responses, and rewards, as well as preliminary data on recidivism. Qualitative data, from both key stakeholders and veteran participants, suggests that offering rehabilitation via various program components, services/referrals, and accountability are critical to the success of the VTC. Data also provides valuable lessons learned for VTC implementation including communication, collaboration, information/protocols, and resources. Performance data shows that a variety of services are utilized and that frequent judicial interaction, drug testing, and sanctions are cornerstones of the VTC. Implications and future directions for research are discussed.     

血栓弹力图在PCI术后患者抗血小板治疗中的应用研究

目的:研究血栓弹力图在经皮冠状动脉介入治疗(PCI)患者中,使用血栓弹力图所测定的血小板抑制率的波动及临床疗效作用。方法:选取我院2012年1月份至2013年12月份收治的200例冠心病PCI治疗患者,应用血栓弹力图分析仪测定其二磷酸腺苷(ADP)途径诱导的血小板抑制率数据,根据抑制率差异分为3组,抑制率70%的为合格组,抑制率30%的为不合格组,入选不合格组再次分为2组,1组保持常规剂量治疗不变,另一组为大剂量治疗组。结果:随访半年的记录,记录一般情况及严重心脏不良事件发生情况。结果:随访的6个月中,共发生不良事件28例,其中合格组10例(9.6%),常规治疗组11例(22.4%),大剂量治疗组7例(14.9%),3组中不良事件发生率比常规治疗组大于大剂量治疗组,大剂量治疗组大于合格组,统计学上有明显差异(P0.05)。结论:血栓弹力图在PCI患者抗血小板治疗中应用具有一定的指导意义。     

动态性与静态性:教学目标的确定及实现——以“教育研究方法”课程为例

教学目标的存在有应然状态和实然状态之分。"教育研究方法"课程的静态目标应具体体现为"涵养科学精神、问题意识的形成、基本研究技能的掌握和有效获取文献信息",这些目标在实现过程中必然存在着动态性选择。     

宏观经济学教学方法探讨

本文分析宏观经济学的自身特点,并据此提出相应的有效的教学方法。     

A comparison of recent nonparametric methods for testing effects in two-by-two factorial designs

The two-way two-levels crossed factorial design is a commonly used design by practitioners at the exploratory phase of industrial experiments. The F-test in the usual linear model for analysis of variance (ANOVA) is a key instrument to assess the impact of each factor and of their interactions on the response variable. However, if assumptions such as normal distribution and homoscedasticity of errors are violated, the conventional wisdom is to resort to nonparametric tests. Nonparametric methods, rank-based as well as permutation, have been a subject of recent investigations to make them effective in testing the hypotheses of interest and to improve their performance in small sample situations. In this study, we assess the performances of some nonparametric methods and, more importantly, we compare their powers. Specifically, we examine three permutation methods (Constrained Synchronized Permutations, Unconstrained Synchronized Permutations and Wald-Type Permutation Test), a rank-based method (Aligned Rank Transform) and a parametric method (ANOVA-Type Test). In the simulations, we generate datasets with different configurations of distribution of errors, variance, factor's effect and number of replicates. The objective is to elicit practical advice and guides to practitioners regarding the sensitivity of the tests in the various configurations, the conditions under which some tests cannot be used, the tradeoff between power and type I error, and the bias of the power on one main factor analysis due to the presence of effect of the other factor. A dataset from an industrial engineering experiment for thermoformed packaging production is used to illustrate the application of the various methods of analysis, taking into account the power of the test suggested by the objective of the experiment.     

Semi-doubly optimal concentric circles fitting with presence of heteroscedasticity

Previous studies focus on homogeneous and isotropic assumptions about the noisy data. Many methods have been developed recently for fitting concentric circles to data. In this paper, these statistical assumptions have been relaxed. To the best of our knowledge, only one iterative method has been recently developed. Due to its complexity, no such algorithm is available to compute the reliable maximum likelihood estimator (MLE). Accordingly, we have developed four new methods that outperform the existing methods including the orthogonal distance regression (ODR). We also discuss which of these methods is superior according to the four principles: statistical efficiency, accuracy, robustness, and computational efficiency. Numerical experiments on synthetic and real images have been conducted to validate our findings.     

Relations Between Alphabetized Name Order and Nomination Counts in Peer Nomination Measures

Peer nominations, a central method for measuring peer relationships in developmental research, typically involve asking children or adolescents to choose peers who fit various criteria from an alphabetized roster of classmates or grade‐mates. Although such measures have been used for decades, very little research has investigated the effects of alphabetical name order on the number of nominations received by peers. This study collected peer nominations for 20 items among 607 eighth grade participants in two schools. Regression analyses showed that earlier name order significantly predicted higher nomination counts for eight of the items, and explained over 5 percent of the variance in four affective variables (friendship, acceptance, acquaintanceship, and received liking). Across variables, name order effects were negatively correlated with internal reliability of nominations, implying that order effects may be related to the consensus of the peer group. Name order also had a minimal effect on inter‐correlations among a subset of variables. Implications and concrete recommendations for controlling and reducing name order effects in future research are discussed.     

Application of a QMRA Framework to Inform Selection of Drinking Water Interventions in the Developing Context

The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long‐term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water‐related context.