Using Analysis of Variance and Factor Analysis for the Reduction of High Dimensional Variation in Time Series of Energy Consumption

Summary: In this paper the complexity of high dimensional data with cyclical variation is reduced using analysis of variance and factor analysis. It is shown that the prediction of a small number of main cyclical factors is more useful than forecasting all the time-points separately as it is usually done by seasonal time series models. To give an example for this approach we analyze the electricity demand per quarter of an hour of industrial customers in Germany. The necessity of such predictions results from the liberalization of the German electricity market in 1998 due to legal requirements of the EC in 1996.     

Lean-healthcare approach to reduce costs in a sterilization plant based on surgical tray rationalization

Abstract

Sterilization plants process all reusable materials used in hospitals during different stages of healthcare provision. Most items sterilized come from the surgical theater in the form of individual instruments, linen and surgical trays. Reducing the number of instruments in trays impacts on the performance of the sterilization process. Here, we propose a three-phase method, based on lean healthcare principles, cluster analysis and kaizen groups of experts to rationalize surgical trays, reducing sterilization processing costs. We innovate by proposing a strategy to approach tray rationalization prioritizing surgical specialties that are both complex and frequent, and by using group technology to cluster surgical trays expediting expert analyses carried out by kaizen groups. Our propositions were tested in a high complexity, tertiary care hospital, covering 12 surgical specialties, reducing the number of instruments by average 9.75%, and the time-to-assemble trays by average 9.68%, obtaining annual savings of US$285.756,00 in sterilization processing costs.     

Statistical data integration using multilevel models to predict employee compensation

This article considers the case where two surveys collect data on a common variable, with one survey being much smaller than the other. The smaller survey collects data on an additional variable of interest, related to the common variable collected in the two surveys, and out-of-scope with respect to the larger survey. Estimation of the two related variables is of interest at domains defined at a granular level. We propose a multilevel model for integrating data from the two surveys, by reconciling survey estimates available for the common variable, accounting for the relationship between the two variables, and expanding estimation for the other variable, for all the domains of interest. The model is specified as a hierarchical Bayes model for domain-level survey data, and posterior distributions are constructed for the two variables of interest. A synthetic estimation approach is considered as an alternative to the hierarchical modelling approach. The methodology is applied to wage and benefits estimation using data from the National Compensation Survey and the Occupational Employment Statistics Survey, available from the Bureau of Labor Statistics, Department of Labor, United States.     

Central exit examinations increase performance... but take the fun out of mathematics

We study the causal effect of state-mandated (central) exit examinations (CEEs) on student performance in Germany and find a small positive effect. We also investigate what actually drives this effect. We find that the teachers’ main reaction to CEEs is to increase the amount of homework and to check and discuss homework more often. Students report increased learning pressure, which has sizeable negative effects on student attitudes toward learning. Students who take central exit exams in mathematics like mathematics less, think it is less easy, and are more likely to find it boring.     

Too much information? Predictors of information overload in the context of online news exposure

As the Internet provides massive amounts of heterogeneous information, people may perceive this medium as challenging. The difficulty to evaluate and select relevant information increases as more and more diverse sources and content are available. Information overload (IO) may be the consequence. The research presented here gives a first comprehensive overview of possible indicators for IO in the context of online news exposure. Based on an online survey (N=419), we found that younger people with less information-seeking self-efficacy were more susceptible to experience IO. Additionally, we identified motivations for media consumption and information retrieval strategies in the Internet that imply IO. With our results, we contribute to a further understanding of IO and provide an important basis for future research needed to face the challenges resulting from the rising media diversity.     

Child welfare workers go to court: The impact of race, gender, and education on the comfort with legal issues

This study examines perceptions of 425 public and private agency child welfare workers from one state in terms of their level of comfort with the court work components of their jobs, at baseline, which is after their initial training but before beginning their child welfare work, and again after six months on the job. Bivariate and multivariate analyses were undertaken. Bivariate analyses reveal that being older and male were associated with higher court comfort levels at baseline and at six months. Being white was associated with higher comfort levels at six months. In addition, private agency workers were more comfortable with court at baseline and six months. Workers with a social work education had higher court comfort levels at baseline and six months, when compared to those with criminal justice or other education. In the multivariate analysis, there were no significant differences in level of comfort with court work based upon worker characteristics at baseline. However, at six months on the job, predictors of comfort with child welfare work were being white and being male; having a social work education approached statistical significance. When change in comfort level was examined, the only significant positive predictor of court comfort was having a social work education.     

Working in Multidisciplinary Community Mental Health Teams: The Impact on Social Workers and Health Professionals of Integrated Mental Health Care

Correspondence to Professor John Carpenter, Centre for Applied Social Studies, University of Durham, Elvet Riverside II, Durham DH1 3JT, UK. E-mail: J.S.W.Carpenter{at}dur.ac.uk Summary This study investigated the relationships between the organizationof community mental health services and professional and teamidentification, team functioning and the psychological well-beingand job satisfaction of staff working in multidisciplinary communitymental health teams (CMHTs). Staff in four districts in theNorth of England completed anonymous questionnaires on two occasions,twelve months apart. There were systematic differences in teamfunctioning, favouring teams in districts where mental healthand social care services were integrated. However, service organizationhad no evident impact on professional or team identificationor on outcomes for staff in terms of stress or job satisfaction.There were differences between social workers (n = 31) and healthservice professionals (n = 82) indicating that social workershad poorer perceptions of team functioning and experienced higherlevels of role conflict. Controlling for other factors includingthe study districts, role conflict was a significant predictorof stress and of job dissatisfaction, while role clarity promotedjob satisfaction. We conclude that support and supervision aimedat ensuring a social work contribution to multidisciplinaryworking should be provided in the course of establishing CMHTsand integrated health and social care services.     

Graphic Family Therapy: An Affective Alternative to Structure and Strategy1

A self-discovery hypothesis regarding changing family dysfunctioning is suggested. From this hypothesis a method for treatment called Graphic Family Therapy has been developed. The four stages of this design—Analysis, Motivation, Evaluation and Research—are discussed. Specific graphic exercises for eight categories of family dysfunction are described. Two illustrative cases, one long-term and one short-term, are presented. Conclusions regarding results, future research, training and other clinical applications are offered.