Employees’ prosocial behavioral intentions through empowerment in CSR decision-making

This study theorizes and empirically tests a conceptual framework to understand how a company can better motivate its employees to carry out persistent prosocial behavior and develop positive organization-employee relationships through corporate social responsibility (CSR) involvement. A managerial approach, employee participative decision making in CSR, is examined for its impact on the prosocial behavioral outcome among employees and the relational outcome for the organization. Furthermore, a psychological mechanism that emphasizes employees’ perceived need satisfaction is examined as the underlying explanation that drives the effectiveness of the managerial approach. The study results support that empowering employees to co-construct CSR decisions with top management is effective in satisfying employees’ basic psychological needs for autonomy, competence, and relatedness. This in turn increases the employees’ intention to maintain long-lasting involvement in CSR and improves their relationships with the company. This study provides important implications for public relations professionals and organizational leaders on how to improve their internal CSR communication and involvement practice and cultivate desirable organization-employee relationships.     

国际社会打击索马里海盗的法律分析

为维护国际海运安全,国际社会纷纷派出军舰赴索马里海域参加打击海盗的行动。这一行动的国际法依据是联合国安理会的授权、海洋法公约的相关规定和索马里过渡政府的同意,且三个因素相互关联。同时打击海盗的行动应受到相关国际法的约束,包括履行尊重沿岸国主权的义务、遵守人道主义法则的义务和因国际不法行为造成损失的赔偿责任。     

Confidence interval estimation of the difference between paired AUCs based on combined biomarkers

In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice.     

澳洲台湾移民居住地选择的初探

本文针对悉尼和布里斯本两个都市之台湾移民的分布及居住迁徙作深入研究。主要透过深入访谈的方法 ,系统性的针对台湾移民选择居住地的因子及决策过程进行探讨 ,并尽量以社会地理学“局内人”的观点 ,架构居住地改变和选择的逻辑来思考整个迁徙过程的机制。研究结果显示 ,随着时间的改变 ,作迁徙决策时所考量的因子也会改变。刚到澳洲时 ,选择居住地的因子主要会考量亲友意见 ;随着经验的累积及对周遭环境的熟悉 ,个别差异性开始凸显 ,每个人对居住地的选择会有不同的考量与分析。在迁居上 ,有向双拼式建筑或都市公寓型房子搬迁的趋势     

An intuitive risk factors search algorithm: usage of the Bayesian network technique in personalized medicine

The article focuses on the application of the Bayesian networks (BN) technique to problems of personalized medicine. The simple (intuitive) algorithm of BN optimization with respect to the number of nodes using naive network topology is developed. This algorithm allows to increase the BN prediction quality and to identify the most important variables of the network. The parallel program implementing the algorithm has demonstrated good scalability with an increase in the computational cores number, and it can be applied to the large patients database containing thousands of variables. This program is applied for the prediction for the unfavorable outcome of coronary artery disease (CAD) for patients who survived the acute coronary syndrome (ACS). As a result, the quality of the predictions of the investigated networks was significantly improved and the most important risk factors were detected. The significance of the tumor necrosis factor-alpha gene polymorphism for the prediction of the unfavorable outcome of CAD for patients survived after ACS was revealed for the first time.     

Testing for bioequivalence of highly variable drugs from TR‐RT crossover designs with heterogeneous residual variances

Traditional bioavailability studies assess average bioequivalence (ABE) between the test (T) and reference (R) products under the crossover design with TR and RT sequences. With highly variable (HV) drugs whose intrasubject coefficient of variation in pharmacokinetic measures is 30% or greater, assertion of ABE becomes difficult due to the large sample sizes needed to achieve adequate power. In 2011, the FDA adopted a more relaxed, yet complex, ABE criterion and supplied a procedure to assess this criterion exclusively under TRR‐RTR‐RRT and TRTR‐RTRT designs. However, designs with more than 2 periods are not always feasible. This present work investigates how to evaluate HV drugs under TR‐RT designs. A mixed model with heterogeneous residual variances is used to fit data from TR‐RT designs. Under the assumption of zero subject‐by‐formulation interaction, this basic model is comparable to the FDA‐recommended model for TRR‐RTR‐RRT and TRTR‐RTRT designs, suggesting the conceptual plausibility of our approach. To overcome the distributional dependency among summary statistics of model parameters, we develop statistical tests via the generalized pivotal quantity (GPQ). A real‐world data example is given to illustrate the utility of the resulting procedures. Our simulation study identifies a GPQ‐based testing procedure that evaluates HV drugs under practical TR‐RT designs with desirable type I error rate and reasonable power. In comparison to the FDA's approach, this GPQ‐based procedure gives similar performance when the product's intersubject standard deviation is low (≤0.4) and is most useful when practical considerations restrict the crossover design to 2 periods.     

Seeking Clarity and Confidence in the Divorce Decision-Making Process

There is a well-established literature dedicated to why couples divorce, transitions associated with divorce, and the impact of divorce on families. However, little is known about the divorce decision-making process. We conducted in-depth interviews with individuals who have recently considered divorce (n = 30) and asked specifically about the roles of 2 concepts in their decision-making process: clarity and confidence. Three major themes emerged from the data: (a) Clarity about a decision to divorce or stay married is desired, it fluctuates, and takes time to find; (b) pivotal moments can bring clarity; and (c) confidence (in the final decision) is desired. Clinical implications and directions for future research are discussed.     

Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models

In this paper, we develop a new estimation procedure based on quantile regression for semiparametric partially linear varying-coefficient models. The proposed estimation approach is empirically shown to be much more efficient than the popular least squares estimation method for non-normal error distributions, and almost not lose any efficiency for normal errors. Asymptotic normalities of the proposed estimators for both the parametric and nonparametric parts are established. To achieve sparsity when there exist irrelevant variables in the model, two variable selection procedures based on adaptive penalty are developed to select important parametric covariates as well as significant nonparametric functions. Moreover, both these two variable selection procedures are demonstrated to enjoy the oracle property under some regularity conditions. Some Monte Carlo simulations are conducted to assess the finite sample performance of the proposed estimators, and a real-data example is used to illustrate the application of the proposed methods.     

On the estimation of a sensitive quantitative mean using blank cards

In this article, we introduce for the first time, the blank card methods for estimation of finite population mean of a sensitive variable. Two generic randomization devices are suggested, and for each device we identify the choices of special models. We introduce additive, multiplicative, and combination of both additive and multiplicative scrambling models that require use of a non sensitive variable. We derive the basic statistical properties of each model. It is interesting to note that various existing estimators can be viewed as the special cases of those presented here. The statistical efficiency of proposed techniques is compared with Greenberg et al. (1971 Greenberg, B.G., Kuebler Jr, R.R., Abernathy, J.R., Horvitz, D.G. (1971). Application of the randomized response technique in obtaining quantitative data. J. Am. Stat. Assoc. 66(334):243–250.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and modified Perri (2008 Perri, P.F. (2008). Modified randomized devices for Simmons’ model. Model Assisted Stat. Appl. 3(3):233–239. [Google Scholar]) model. The proposed devices can easily be adjusted to achieve the required efficiency level by making suitable choices of different design parameters.     

Parametric bootstrap inferences for the growth curve models with intraclass correlation structure

This paper presents parametric bootstrap (PB) approaches for hypothesis testing and interval estimation of the fixed effects and the variance component in the growth curve models with intraclass correlation structure. The PB pivot variables are proposed based on the sufficient statistics of the parameters. Some simulation results are presented to compare the performance of the proposed approaches with the generalized inferences. Our studies show that the PB approaches perform satisfactorily for various cell sizes and parameter configurations, and tends to outperform the generalized inferences with respect to the coverage probabilities and powers. The PB approaches not only have almost exact coverage probabilities and Type I error rates, but also have the shorter expected lengths and the higher powers. Furthermore, the PB procedure can be simply carried out by a few simulation steps. Finally, the proposed approaches are illustrated by using a real data example.