On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

On sequential closed testing dose groups with a control

Methods for a sequential test of a dose-response effect in pre-clinical studies are investigated. The objective of the test procedure is to compare several dose groups with a zero-dose control. The sequential testing is conducted within a closed family of one-sided tests. The procedures investigated are based on a monotonicity assumption. These closed procedures strongly control the familywise error rate while providing information about the shape of the dose-responce relationship. Performance of sequential testing procedures are compared via a Monte Carlo simulation study. We illustrae the procedures by application to a real data set.     

Stop the Beat: Quiet Regulation and Cultural Conflict1

This article explores a recent conflict over the youth phenomenon known as “raving” in the City of Chicago. By interviewing participants involved in the conflict, I set out to understand the extent to which the crackdown on raves in Chicago was similar to earlier social reactions to jazz, comic books, rock and roll, and Dead Head culture, as well as to more recent conflicts over punk, rap music, and raves in other cities. While most previous research on cultural conflict has focused on moral crusades, campaigns, and panics, the Chicago conflict represents an example of “quiet regulation.” Opponents refrained from highly visible, morally charged attacks; instead, in the absence of media hype and visible public discourse, public officials justified the crackdown in highly bureaucratic terms—avoiding risk, collecting taxes, enforcing codes. Nonetheless, they also drew on cultural schemas that linked raves and raving with drugs, sex, and deviance. As a result, officials selected a course of regulation that criminalized DJs and discredited the artform. In the absence of a highly visible moral campaign, the rave participants were unable to mobilize and resist the regulation and defend their lifestyle. Sociologists must move beyond highly visible campaigns and crusades and pay greater attention to quiet regulation, both because such regulation is likely to increase in the future and because it has significant consequences for power, cultural expression, and identity.     

Power and dependence perspectives on outsourcing decisions

Since the 1980s outsourcing has been a major topic in both economic and management literature. Economic literature tends to focus on the transaction cost perspective. In management literature the core competence approach prevails. An emerging alternative view on outsourcing is the power and dependence perspective. Aspects of power and dependence become visible in four case studies involving the maintenance of capital assets. In each instance both the buyer and supplier sides of the dyad are examined. The paper concludes with managerial implications and research opportunities.     

The application of a performance management system in hospitals: A hypothetical example

Abstract

The central theme of this article is performance management, defined as activities of organizations aimed at an effective and efficient use of their human resources. The organization focused on in particular is the hospital. Three principles taken from motivation theory are dealt with which are basic to performance management: goal setting, feedback and reinforcement. Next, a recently developed procedure (Pritchard 1990, Pritchard et al. 1988, 1989) for the design of performance management systems is described. This procedure, ProMES: Productivity Measurement and Enhancement Systems, is explained using a team of ward nurses as a hypothetical example. In addition to the nursing wards example, other potential applications of the ProMES technique to several hospitals areas are mentioned. Finally, some conditions that should be fulfilled in order to successfully start a ProMES project are discussed.     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

Effect of a new selection procedure on adaptive estimation

Adaptive estimation of parameters of some failure time distributionsis considered. A new procedure named the F-procedure has beendeveloped for selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimatorsof parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptiveestimators by simulation of samples using the Monte Carlo method.Adaptive estimation of parameters of some failure time distributions is considered. A new procedure named the F-procedure has been developedfor selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimators of parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptive estimators by simulation of samples using the Monte Carlo method.     

A generalization of the compound rayleigh distribution: using a bayesian method on cancer survival times

In this paper the generalized compound Rayleigh model, exhibiting flexible hazard rate, is high¬lighted. This makes it attractive for modelling survival times of patients showing characteristics of a random hazard rate. The Bayes estimators are derived for the parameters of this model and some survival time parameters from a right censored sample. This is done with respect to conjugate and discrete priors on the parameters of this model, under the squared error loss function, Varian's asymmetric linear-exponential (linex) loss function and a weighted linex loss function. The future survival time of a patient is estimated under these loss functions. A Monte Carlo simu¬lation procedure is used where closed form expressions of the estimators cannot be obtained. An example illustrates the proposed estimators for this model.