Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Using concept mapping as a planning tool: Child welfare citizen review panels

Citizen Review Panels (CRPs) are groups of citizen volunteers authorized by U.S. federal law to examine state child welfare agencies. These groups inspect policies and practices related to child protection responsibilities and are tasked with making recommendations for systemic improvement. Despite the federal mandate for each state to develop a CRP and the potential of these groups to positively impact child welfare practices, there is a dearth in the literature related to CRPs. Consequently, planning and evaluation processes of these groups vary widely. This study reports on the use of concept mapping (CM) to outline a framework for planning and subsequently evaluating the CRP in one southeastern state. CM is a mixed-method research approach that uses multi-dimensional scaling and hierarchical cluster analyses to explore an area of study. Through these analyses, the method creates visual depictions of conceptual relationships between ideas. Data yielded a seven cluster concept map that CRP members (N = 36) utilized for planning processes, and subsequently for developing an internal evaluation tool. Results from this study offer a unifying framework by which CRPs, and similar groups in other areas can utilize for planning and evaluation purposes. After a review of pertinent literature on CRPs, this article explicates CM processes utilized in this study, describes results, discusses lessons learned, and outlines apposite areas for future CRP research.     

On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

The impact of social power and influence on the implementation of innovation strategies: A case study of a UK mega infrastructure construction project

Influence plays a key role in reaching consensus among multiple actors involved in project-based decision-making processes. While prior literature devotes considerable attention to describing influence, little attention has been paid to influence at the individual level of the strategic project manager within the context of megaprojects. This research intended to fill this knowledge gap by identifying and describing the influence strategies that a strategic project manager applies when implementing innovation strategies on megaprojects. A qualitative case study was used to examine the complex social processes involved in a major UK capital investment programme. The findings underline a critical subset of influence strategies, notably higher-management support, inspirational appeal and bargaining. The study proposes a utilitarian structure of social power comprising selective, supportive and executory power bases.     

Integrating Family Resilience and Family Stress Theory

The construct, family resilience, has been defined and applied very differently by those who are primarily clinical practitioners and those who are primarily researchers in the family field. In thisarticle, the family resilience perspective is integrated with conceptual definitions from family stress theory using the Family Adjustment and Adaptation Response (FAAR) Model in an effort to clarify distinctions between family resiliency as capacity and family resilience as a process. The family resilience process is discussed in terms of (a) the meaning of significant risk exposure (vs. the normal challenges of family life) and (b) the importance of making conceptual and operational distinctions between family system outcomes and family protective processes. Recommendations for future family resilience research are discussed.     

阅读与语篇理解的相关理论分析

阅读是外语教学和学习中的重要环节。阅读不仅是读者知识积累和经验积淀的反映,而且可以构架起作者和读者之间沟通的桥梁。掌握了语篇生成的理论基础和技巧,读者就能在阅读中驾轻就熟地理解作者的意图和观点,从而达到理解语篇的目的。     

具有带误差逼近的赋值伪压缩映像的公共不动点迭代序列

在实一致光滑Banach空间中引入了一类新的逼近三个极值强伪压缩映象唯一公共不动点的带误差迭代序列,以及通过Petryshyn不等式讨论了该带误差迭代序列的收敛性.     

王夫之对义、利的层次性及相对性的分析

义利观问题是中国伦理思想史的核心问题之一，历代思想家都十分重视对它的研究。王夫之在总结、继承前哲义利思想的基础上，提出了自己的义利观，并对义利进行了层次性及相对性的分析，既继承了传统道义论的精华，又极大地丰富了中国古代伦理思想的内涵。     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.