The Social Work Assessment Tool (SWAT)

This paper reports on the last of three National Hospice and Palliative Care Organization initiatives to move hospice and palliative care social workers into the patient/family outcomes arena: the development of the Social Work Assessment Tool. The experience of a team of practitioners and researchers is described, including results of two pilot studies and subsequent SWAT revisions. The major focus is on the current model performance improvement project, in which 19 social workers from 14 hospice and palliative care programs used the SWAT with 101 patients and 81 primary caregivers for a median of 44 days. Quantitative analysis indicated significant improvement in SWAT scores for patients from the first to the second social work visit (t = -2.60, df = 47, p .01). Qualitative interviewing of the social workers indicated some lack of readiness in the field to conduct quantitative outcomes measurement. Additional measures are needed in addition to the SWAT, including qualitative measures, and measures of mezzo and macro practice. Participants indicated that the SWAT was appropriate for use with economically and culturally diverse clients.     

Design of Stockless Production Systems

In make‐to‐stock production systems finished goods are produced in anticipation of demand. By contrast, in stockless production systems finished goods are not produced until demand is observed. In this study we investigate the problem of designing a multi‐item manufacturing system, where there is both demand‐ and production‐related uncertainty, so that stockless operation will be optimal for all items. For the problem of interest, we focus on gaining an understanding of the effect of two design variables: (i) manufacturing speed—measured by the average manufacturing rate or, equivalently, the average unit manufacturing time, and (ii) manufacturing consistency—measured by the variation in unit manufacturing times. We establish conditions on these two variables that decision makers can use to design stockless production systems. Managerial implications of the conditions are also discussed.     

Efficiency in Games With Markovian Private Information

We study repeated Bayesian games with communication and observable actions in which the players' privately known payoffs evolve according to an irreducible Markov chain whose transitions are independent across players. Our main result implies that, generically, any Pareto‐efficient payoff vector above a stationary minmax value can be approximated arbitrarily closely in a perfect Bayesian equilibrium as the discount factor goes to 1. As an intermediate step, we construct an approximately efficient dynamic mechanism for long finite horizons without assuming transferable utility.     

论全球化的合理利用

20世纪70年代以来,多国公司寻求在世界范围内安排其生产经营活动,于是多国公司成为全球化的支持者和主体;而全球化的反对者认为在世界一体化迅速发展的同时,许多国家不再能够采取主权国家政策,尤其是在社会保障方面。不同国家对于全球化的态度不尽相同,但是某些国家却把其面临的经济困境归咎于全球化。相反,本文表明,国家对国际贸易的开放为国家经济的发展提供了更多选择,并且是解决许多国家在2 0世纪70～80年代遭遇的经济困难的良方。因此,许多发达国家和发展中国家不同程度地扩大了开放。文章指出了国家的公共政策是促进全球化的积极影响…     

Nonparametric Predictive Inference for Ordinal Data

Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, made possible by the use of lower and upper probabilities. In this article, NPI is presented for ordinal data, which are categorical data with an ordering of the categories. The method uses a latent variable representation of the observations and categories on the real line. Lower and upper probabilities for events involving the next observation are presented, and briefly compared to NPI for non ordered categorical data. As application, the comparison of multiple groups of ordinal data is presented.     

On Blest’s Measure of Kurtosis Adjusted for Skewness

We reconsider the derivation of Blest’s (2003) skewness adjusted version of the classical moment-based coefficient of kurtosis and propose an adaptation of it which generally eliminates the effects of asymmetry a little more successfully. Lower bounds are provided for the two skewness adjusted kurtosis moment measures as functions of the classical coefficient of skewness. The results from a Monte Carlo experiment designed to investigate the sampling properties of numerous moment-based estimators of the two skewness adjusted kurtosis measures are used to identify those estimators with lowest mean squared error for small to medium sized samples drawn from distributions with varying levels of asymmetry and tailweight.     

Effective Rotation Patterns Under Non Response in Two-Occasion Successive Sampling

This article intends to develop some effective rotation patterns with the aid of attractive imputation methods when the problems of non response occur in two-occasion successive sampling. Utilizing the information on p (p ??1) auxiliary variables regression methods of imputation have been considered and subsequently multiple linear regression type estimators are proposed to estimate the current population mean in two-occasion successive sampling. Proposed estimators are compared with the estimator for same situations but in the absence of non-response. Optimum replacement strategies of the respective estimators have been discussed and results are interpreted with the help of empirical studies. Conclusions and suitable recommendations are made.     

On the use of several auxiliary variables in estimation of current population mean in successive sampling

ABSTRACT

The present work intends to put emphasis on the role of several auxiliary variables on both the occasions to improve the precision of estimates at current occasion in two-occasion successive sampling. Utilizing the readily available information on several auxiliary variables on both occasions and the information on study variable from the previous occasion, an efficient estimation procedure of population mean on current occasion has been suggested. Optimum replacement strategy and the efficiencies of the proposed estimator have been discussed. Empirical studies are carried out, and appropriate recommendations have been put forward for practical applications.     

Ridge Autoregression Estimation: LS Method

In an AR (p)-model, least-squares estimation of the parameters is considered when it is suspected that the parameters may belong to a linear subspace and the estimated covariance matrix is ill-conditioned. Accordingly, we define five estimators and study their properties in an asymptotic setup to discover dominance properties based on asymptotic distributional bias (ADB), MSE (ADMSE) matrices, and under quadratic risks (ADQR).