Combining two classical approaches for statistical selection

This paper presents a selection procedure that combines Bechhofer's indifference zone selection and Gupta's subset selection approaches, by using a preference threshold. For normal populations with common known variance, a subset is selected of all populations that have sample sums within the distance of this threshold from the largest sample sum. We derive the minimal necessary sample size and the value for the preference threshold, in order to satisfy two probability requirements for correct selection, one related to indifference zone selection, the other to subset selection. Simulation studies are used to illustrate the method.     

A robust posterior preference multi-response optimization approach in multistage processes

Nowadays, many manufacturing and service systems provide products and services to their customers in several consecutive stages of operations, in each of which one or more quality characteristics of interest are monitored. In these environments, the final quality in the last stage not only depends on the quality of the task performed in that stage but also is dependent on the quality of the products and services in intermediate stages as well as the design parameters in each stage. In this paper, a novel methodology based on the posterior preference approach is proposed to robustly optimize these multistage processes. In this methodology, a multi-response surface optimization problem is solved in order to find preferred solutions among different non dominated solutions (NDSs) according to decision maker's preference. In addition, as the intermediate response variables (quality characteristics) may act as covariates in the next stages, a robust multi-response estimation method is applied to extract the relationships between the outputs and inputs of each stage. NDSs are generated by the ?-constraint method. The robust preferred solutions are selected considering some newly defined conformance criteria. The applicability of the proposed approach is illustrated by a numerical example at the end.     

Selection of the best in 2×2 factorial designs

Selection of the cell in a 2×2 -factorial design with the greatest mean is considered. A general class of ranking and selection procedures (RSP) is constructed to include methods based on the largest marginal cell means (SP1) or on the largest cell mean (SP3). Using the preference zone approach the minimum probability of a correct solution is found, In this paper a RSP which maximizes the minimum probability of a correct solution over the preference zone is found. In this way selection of the cell with the greatest observed mean is proven to be admissible.     

Risk preference and employment contract type

Summary.  We explore the possibility that a systematic relationship exists between employment within a particular type of contract and risk preference. We exploit a set of proxies for risk preference, whereby some of the proxies capture risk loving behaviour (expenditure on gambling, smoking and alcohol) whereas others capture risk averse behaviour (expenditure on life and contents insurance, and unearned income). The empirical analysis, based on pooled cross-section data from the UK Family Expenditure Survey, 1997–2000, provides evidence of a systematic relationship between employment contract type and risk preference, with, for example, self-employed workers being more or less likely to engage in the consumption of 'risky' or financial security products respectively. The results are based on the ordered generalized extreme value model, a relatively infrequently used discrete choice model, which allows for ordering and correlation in the alternatives observed.     

A New PC-Based Test for Varian's Weak Separability Conditions

This article develops a new method to evaluate revealed preference separability conditions. In contrast to previous studies, our results generally find weak separability, even when datasets have some measurement error. In addition, revealed preference and weak separability appear robust to measurement error, different price distributions, and alternative preference settings. Measurement error generally results in relatively few violations of revealed preference or weak separability.     

Ordering k-out-of-n systems with interdependent components and one active redundancy

This paper studies the optimal allocation of one active redundancy to a k-out-of-n system in the context of statistically dependent component lifetimes. It is proved that assigning the redundancy to the weakest component is more favorable so as to get a larger system lifetime in terms of both the usual stochastic order and the stochastic preference order.     

△-correct decision for location and scale parameters

In selecting t out of k populations, a △-correct decision is said to be made if the smallest location parameter for the selected populations is not more than △ below the largest location parameter for the non-selected populations. (For seal? parameters there is a similar definition in terms of ratio3.) The minimum probability of △-correct decision over the entire parameter pace is shown to be equal to the minimum probability of correct selection over a preference zone determined by △.     

A Bayesian approach to the statistical analysis of device preference studies

Drug delivery devices are required to have excellent technical specifications to deliver drugs accurately, and in addition, the devices should provide a satisfactory experience to patients because this can have a direct effect on drug compliance. To compare patients' experience with two devices, cross-over studies with patient-reported outcomes (PRO) as response variables are often used. Because of the strength of cross-over designs, each subject can directly compare the two devices by using the PRO variables, and variables indicating preference (preferring A, preferring B, or no preference) can be easily derived. Traditionally, methods based on frequentist statistics can be used to analyze such preference data, but there are some limitations for the frequentist methods. Recently, Bayesian methods are considered an acceptable method by the US Food and Drug Administration to design and analyze device studies. In this paper, we propose a Bayesian statistical method to analyze the data from preference trials. We demonstrate that the new Bayesian estimator enjoys some optimal properties versus the frequentist estimator.     

Comparison of estimators of the location parameter using pitman's closeness criterion

Necessary and sufficient conditions for a linear estimator to dominate another linear estimator of a location parameter under the Pitman's criterion of comparison are discussed. Consequently it is demonstrated that a linear biased estimator can not dominate a linear unbiased estimator under Pitman's criterion and that the sample mean is the Closest Linear Unbiased Estimator (CLUE). It is also shown that the ridge regression estimator with a known biasing constant can not dominate the ordinary least squares estimator. If an estimator δdominates an estimator δin the average loss sense then sufficient conditions are obtained under which δis also preferred over δunder Pitman's criterion. Further we obtain sufficient conditions under which preference under the Pitman's criterion will lead to preference under the mean squared error sense.     

一类具有补偿的采购供应链中供应商R&D投资决策分析

在建立具有补偿的采购供应链R&D投资规模调控模型的基础上,对采购中供应商的R&D投资决策均衡进行研究,着重探讨采购商的决策偏好和供应商的行动顺序对投资均衡的影响。所得结论表明:在一定的条件下,供应商对R&D项目的投资均衡为采购商所希望的均衡,但是,当采购商对供应商的投资行为存在决策偏好时,无论供应商先行动还是后行动,供应商的投资均衡将会偏离采购商所希望的均衡。     

An Exponential-Family Multidimensional Scaling Mixture Methodology

A multidimensional scaling methodology (STUNMIX) for the analysis of subjects' preference/choice of stimuli that sets out to integrate the previous work in this area into a single framework, as well as to provide a variety of new options and models, is presented. Locations of the stimuli and the ideal points of derived segments of subjects on latent dimensions are estimated simultaneously. The methodology is formulated in the framework of the exponential family of distributions, whereby a wide range of different data types can be analyzed. Possible reparameterizations of stimulus coordinates by stimulus characteristics, as well as of probabilities of segment membership by subject background variables, are permitted. The models are estimated in a maximum likelihood framework. The performance of the models is demonstrated on synthetic data, and robustness is investigated. An empirical application is provided, concerning intentions to buy portable telephones.     

学历和性别对劳动者工资的影响研究

随着教育特别是高等教育的迅速发展,我国高学历人才培养规模呈现膨胀趋势,从而学历对于劳动者是否具有作用成为民众越来越关注的议题。本文首先从利润最大化角度分析企业支付给不同学历劳动者工资意愿的差异,这将作为实证检验学历影响劳动者工资的理论支撑,接着运用2004年中国工业经济普查数据分行业检验不同学历劳动者平均工资的差异,并且关注劳动者性别对工资所可能存在的影响,其中学历共分为初中、高中、大专、本科与研究生五种。检验结论认为：（1）高中学历、大专学历与本科学历对于劳动者工资具有积极影响,并且这种影响较为稳定并逐渐增强,而研究生学历对于劳动者工资的影响难以确定;（2）在运用教育赋分法衡量企业平均学历后,检验认为在平均学历保持不变的情况下,女性员工所占比率对企业所支付的人均工资可能存在负向影响,并且员工平均学历对人均工资的正向影响可能会随着女性员工比率提高而减弱。     

Book-a-Book: Facilitating Access to Learning Materials for Students With Disabilities

Abstract

Until 2019, each higher education institution in Flanders had to develop their own workflows to handle requests for digital study materials for students with disabilities. At KU Leuven these requests are processed by KU Leuven Libraries Central Services. This unit, among other things, supports the core tasks of KU Leuven Libraries in the area of acquisitions and licensing negotiations with publishers. This article will focus on the creation and development of Book-a-Book, which has its origin in the service the KU Leuven Libraries Central Services has been providing for students with disabilities for KU Leuven students since 2011. Book-a-Book is a web application that facilitates access to learning materials for students with disabilities enrolled in Flemish higher education institutions. It is the first online tool to serve all higher education students with disabilities in Flanders and is the result of a collaboration between The Support Center for Inclusive Higher Education (SIHO), KU Leuven Libraries, and LIBIS (Leuven Integrated Library and Information System). SIHO is as a collaboration between the associations of the Flemish universities and colleges on the one side, and the Flemish government on the other side. The core responsibility of the SIHO lies in the support of all higher education institutions in realizing inclusive higher education for students with a disability. On September 12, 2019, Book-a-Book was launched on the international conference “Enhancing Student Experience: Innovative Support Tools for Students with Disabilities” in Brussels, Belgium.     

Families of splitting criteria for classification trees

Several splitting criteria for binary classification trees are shown to be written as weighted sums of two values of divergence measures. This weighted sum approach is then used to form two families of splitting criteria. One of them contains the chi-squared and entropy criterion, the other contains the mean posterior improvement criterion. Both family members are shown to have the property of exclusive preference. Furthermore, the optimal splits based on the proposed families are studied. We find that the best splits depend on the parameters in the families. The results reveal interesting differences among various criteria. Examples are given to demonstrate the usefulness of both families.     

代次视角下农民工组织参与对政治参与意愿的影响研究——基于西安市1215名农民工的调查

利用2012年“西安市农村流动人口发展状况调查”数据,使用卡方检验和二分Logistic回归,在代次视角下分析农民工政治参与意愿的特征和组织参与对农民工政治参与意愿的影响.研究发现:农民工政治参与意愿具有稳定的制度性偏好,但新生代农民工非制度化参与的风险增加;组织化能够显著提升农民工的政治参与意愿,随着代次更替,作用方向不变,但程度减弱;农民工经济收入的增加,具有同时促进制度化和抑制非制度化参与倾向的作用.     

Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

Econometric approaches to the specification of life cycle labour supply and commodity demand behaviour

Many of the recently developed alternative econometric approaches to the construction and estimation of life-cycle consistent models using individual data can be viewed as alternative choices for conditioning variables that summarise past decisions and future anticipations. By ingenious choice of this conditioning variable and by exploitation of the duality relationships between the alternative specifications, many currently available micro-data sets can be used for the estimation of life-cycle consistent models. In reviewing the alternative approaches their stochastic properties and implict preference restrictions are highlighted. Indeed, empirical specifications that are parameterised in a form of direct theoretical interest often can be shown to be unnecessarily restrictive while dual representations may provide more flexible econometric models. These results indicate the particular advantages of different types of data in retrieving life-cycle consistent preference parameters and the appropriate, most flexible, econometric approach for each type of data. A methodology for relaxing the intertemporal separability assumption is developed and the advantages and disadvantages of alternative approaches in this framework are considered.     

James-Stein Estimation from an Alternative Perspective

In the comparison of estimators, the typical viewpoint of mean squared error has been challenged by C. R. Rao. In this article we propose a method of selecting estimators in normal populations based on their regions of preference. These regions of preference are a natural consequence of Rao's emphasis on Pitman nearness. We apply the method in the case of estimation of the mean of a bivariate normal through the James-Stein class.     

中国货币政策的非对称性偏好调控模式及其演变研究

非对称性实现物价稳定和经济增长是央行调控宏观经济的普遍策略，本文基于非对称性福利损失函数，首次通过逆推实现央行时变非对称性偏好调控模式估计。结果表明，央行在调控通胀和通胀波动目标上表现出较强的政策取向，同时，存在厌恶通胀和规避经济收缩的时变非对称性偏好，由此也使得央行具有较强的动机维护实际通胀低于通胀目标以及实际经济增速高于经济增长目标。特别是，央行在厌恶通胀和规避经济衰退上的非对称性偏好呈现出较强的此消彼长关系。此外，近年来央行厌恶通胀的非对称性偏好持续走强，而规避经济收缩的非对称性偏好却逆向变弱，表明我国货币政策具有较强的治理通胀偏好，但维持经济增速高于增速目标的政策取向却有所减弱。     

Beer chemistry and canadians' beer preferences

Beer companies want to understand the relationship between the chemical characteristics of beer and the preferences for beer exhibited by consumers. Two data sets were provided to the analysts in this case study. The first set consisted of chemical measurements on 91 beers and preference measurements on the same beers collected from beer consumers in blind taste tests. The analysts were asked to use these data to develop a statistical model relating beer chemistry and consumer preferences for beer. The second data set consisted of chemical measurements on a holdout sample of 37 beers. The analysts were asked to employ their statistical model to predict consumer preferences for the beers in the holdout sample. The case study assesses the success of their modelling efforts.