Hierarchical bayes quality measurement plan

Quality Measurement Plan (QMP) as developed by Hoadley (1981) is a statistical method for analyzing discrete quality audit data which consist of the expected number of defects given the standard quality. The QMP is based on an empirical Bayes (EB) model of the audit sampling process. Despite its wide publicity, Hoadley's method has often been described as heuristic. In this paper we offer an hierarchical Bayes (HB) alternative to Hoadley's EB model, and overcome much of the criticism against this model. Gibbs sampling is used to implement the HB model proposed in this paper. Also, the convergence of the Gibbs sampler is monitored via the algorithm of Gelman and Rubin (1992).     

A Compressive Sensing Based Analysis of Anomalies in Generalized Linear Models

In this article, we present a compressive sensing based framework for generalized linear model regression that employs a two-component noise model and convex optimization techniques to simultaneously detect outliers and determine optimally sparse representations of noisy data from arbitrary sets of basis functions. We then extend our model to include model order reduction capabilities that can uncover inherent sparsity in regression coefficients and achieve simple, superior fits. Second, we use the mixed ?₂/?₁ norm to develop another model that can efficiently uncover block-sparsity in regression coefficients. By performing model order reduction over all independent variables and basis functions, our algorithms successfully deemphasize the effect of independent variables that become uncorrelated with dependent variables. This desirable property has various applications in real-time anomaly detection, such as faulty sensor detection and sensor jamming in wireless sensor networks. After developing our framework and inheriting a stable recovery theorem from compressive sensing theory, we present two simulation studies on sparse or block-sparse problems that demonstrate the superior performance of our algorithms with respect to (1) classic outlier-invariant regression techniques like least absolute value and iteratively reweighted least-squares and (2) classic sparse-regularized regression techniques like LASSO.     

Exploring the Importance of Business Clockspeed as a Moderator for Determinants of Supplier Network Performance*

As the importance of supplier networks becomes increasingly recognized as a vital factor to company performance, researchers and practitioners alike are focusing their attention on this subject. The study's main objective is to test the specific hypotheses that effective use of Information Technology (IT) and the depth of company relationships with suppliers are directly related to Supplier Network (SN) performance, and that industry clockspeed moderates these relationships. A convenience sample of 135 manufacturing organizations was used to empirically test these hypotheses. Our results indicate that clockspeed does moderate the relationship between IT use effectiveness and supplier network performance. The same is true in the case of supplier relations depth, and hence, managers are encouraged to pay attention to the items comprising network performance as a determinant of supplier network performance.     

Does “buyer beware” work in migration? Contracting between brokers and migrants in Vietnam

This article is an attempt to open the lid a little of the “black box of migration” i.e. brokers. Analysing contracts between brokers and labour migrants, we identify four different forms of exploitation of migrants by brokers: expropriation of skill premium, risk shifting, over‐charging, and non‐refund of deposits. Opportunistic behaviour by brokers, as evidenced by such exploitation, is seen as a market failure that is explained by human attributes and transactional characteristics. Given the rigidities in the human attributes of the contracting parties and the nature of migration as a risky multi‐period transaction, proposals are made for non‐market interventions, which can lead to more equitable contracting.     

Variance estimation in complex survey sampling for generalized linear models

Summary.  Complex survey sampling is often used to sample a fraction of a large finite population. In general, the survey is conducted so that each unit (e.g. subject) in the sample has a different probability of being selected into the sample. For generalizability of the sample to the population, both the design and the probability of being selected into the sample must be incorporated in the analysis. In this paper we focus on non-standard regression models for complex survey data. In our motivating example, which is based on data from the Medical Expenditure Panel Survey, the outcome variable is the subject's 'total health care expenditures in the year 2002'. Previous analyses of medical cost data suggest that the variance is approximately equal to the mean raised to the power of 1.5, which is a non-standard variance function. Currently, the regression parameters for this model cannot be easily estimated in standard statistical software packages. We propose a simple two-step method to obtain consistent regression parameter and variance estimates; the method proposed can be implemented within any standard sample survey package. The approach is applicable to complex sample surveys with any number of stages.     

Complementary Drivers of New Product Development Performance: Cross‐Functional Coordination,Information System Capability,and Intelligence Quality

Coordination efforts that access and align relevant cross‐functional expertise are regarded as an essential element of innovation success. In recent years, these efforts have been further augmented through complementary investments in information systems, which provide the technological platforms for information sharing and coordination across functional and organizational boundaries. Somewhat overlooked has been the critical mediating role of the intelligence gained through these efforts and capabilities. This study draws on the theory of complementarity to elaborate on the nature of this mediating concept. Theoretical predictions of the model are tested using instrument variable regression analysis of data collected from a sample of publicly traded US manufacturing firms. The findings suggest that the effects of both internal and external coordination on market intelligence and supply‐chain intelligence are moderated by the firm's information system capability. The effect of both types of intelligence quality on new product development performance was contingent with the effects being enhanced (attenuated) when the market conditions were dynamic (stable). The results are robust to common‐method bias, endogeneity concerns, and alternative estimation methods.     

Transitions in Caregiving: Evaluating a Person-Centered Approach to Supporting Family Caregivers in the Community

Caregivers of older adults provide a wide range of informal supports and services that enable older adults to continue living in the community. This study describes the use of a multicomponent intervention combined with a person-centered approach to assist caregivers of older adults in the community. Four hundred and eighteen caregiver and care recipient dyads participated in this study and their outcomes related to burden, depression, well-being, and care recipient functional status were evaluated. The findings suggest that adult child and spousal caregivers experience burden differently. Programs designed to support caregivers must tailor services to the unique needs of adult child and spousal caregivers.     

Review and preview of productivity research and applications

During the last two decades, productivity research and applications have not been given adequate importance when trying to attain excellence in the management of manufacturing enterprises. Recent developments in managerial philosophies Total Quality Management and Business Process Re-engineering , manufacturing technologies Flexible Manufacturing Systems, Computer Integrated Manufacturing, etc. and Information Technology innovations have made the traditional productivity improvement techniques obsolete. This article presents a review consisting of analyses of literature on productivity and a survey of manufacturing enterprises. A five-step preview strategy on productivity is enumerated which provides a meaningful direction towards future productivity research and application. The article is concluded by briefly describing the current research that is being carried out based on the preview strategy evolved.     

Predictive capability of stratified proportional hazards models

Following on from the work of O'Quigley & Flandre (1994) and, more recently, O'Quigley & Xu (2000), we develop a measure, R2, of the predictive ability of a stratified proportional hazards regression model. The extension of this earlier work to the stratified case is relatively straightforward, both conceptually and in its practical implementation. The extension is nonetheless important in that the stratified model is making weaker assumptions than the full multivariate model. Formulae are given that can be readily incorporated into standard software routines, since the component parts of the calculations are routinely provided by most packages. We give examples on the predictability of survival in breast cancer data, modelled via proportional hazards and stratified proportional hazards models, the latter being necessary in view of the effects of a non-proportional hazards nature.