Sweeping,alignment and the analysis of unbalanced data

The terms sweeping and alignment refer to the same process. Sweeping/alignment is used by data analysts as a technique for describing the effects of a model factor (e.g., treatments in a randomized block design) after the effects of nuisance parameters (e.g., blocks) have been removed from the data. In this paper sweeping/alignment is used as the basis for developing tests of factors in unbalanced experimental design models. Formulas are presented for treatment effects in randomized block designs with missing observations, and for interaction and main effects in unbalanced two-way factorial designs with empty cells.     

Data Splitting

Data splitting is the act of partitioning available data into two portions, usually for cross-validatory purposes. One portion of the data is used to develop a predictive model and the other to evaluate the model's performance. This article reviews data splitting in the context of regression. Guidelines for splitting are described, and the merits of predictive assessments derived from data splitting relative to those derived from alternative approaches are discussed.     

A bayesian approach to bioassay. technical report m498

We describe the design and analysis for a simulation experiment to compare the mean-squared errors (MSE's) of two quantile estimators defined for random walk designs. The dependence of the easily computed MSE of the first estimator on the levels of five factors is examined via multiple regression. This information is used to plan a simulation to compute the MSE of the second estimator using a fraction of a 3³5²factorial allowing uncorrelated estimates for all main effects and the two-factor interactions of a specified factor. Efficient estimation of the MSE of the second estimator is attempted through antithetic and control variate techniques of variance reduction, with modest success.     

Psychometric Validation of the Gambling Passion Scale (GPS) in an English-speaking University Sample

The Gambling Passion Scale (GPS) is a recently developed research instrument for assessing individuals' passion for gambling. Because the psychometric properties of the GPS have only previously been examined in French Canadians, the aim of this study was to replicate previous psychometric findings in an English-speaking university sample. Participants (female: n = 58; male: n = 89) were drawn from a university campus based on self-reported experience with gambling indexed by scores on the South Oaks Gambling Screen (SOGS). The two-factor structure reported by Rousseau et al. (Journal of Gambling Studies, 18(1), pp. 45–66, 2002) was largely replicated in this sample, as were relationships between ‘obsessive passion’ and negative consequences stemming from gambling. These results support the validity of the GPS as a measure of gambling passion in English-speaking university gamblers and its potential to contribute to understanding problem gambling.     

Understanding the Kalman Filter

This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if we use a Bayesian formulation and some well-known results in multivariate statistics. We also give a simple example illustrating the use of the Kalman filter for quality control work.     

Undergraduate Social Work Manpower and Job Opportunities: A Regional Study

This study deals with the deployment, utilization, and potential future employment opportunities for bachelor's-level social workers based on a survey of social service agencies in the Dallas-Fort Worth-Denton, Texas metropolitan area. Findings are presented in relation to social service agency reports concerning budgeted and vacant positions for different types of social service personnel, degree and academic fields specified for the positions, estimates concerning future social service personnel positions, preferences in hiring between undifferentiated bachelor's-level personnel and BSWs, and preferences in hiring between BSW and MSW personnel.     

National policy making in a global economy: The case for U.S. economic planning

In 1980 the Joint Economic Committee completed the Special Study on Economic Change. This 20 volume, 3-year project, was premised on the fact that: ‘fundamental economic, social, political, international and technical conditions have changed, and are still changing markedly’. This suggests that conventional wisdom and established economic tools may not be equal to meeting the challenge of making sound policies in the economic sphere. The so-called laws of economics have not been repealed, but all guiding principles presuppose a certain environment of conditions, customs and practices—and when these change, the implementation of new policies and the modes of adjustment have to change also. This paper examines the problem of devising policy instruments for economic management, identifying the facts of the changing economic environment and the main difficulties facing world economic development.     

The business portfolio approach—Where it falls down in practice

During the past decade the SBU (or portfolio) concept has enjoyed widespread popularity as a basis for corporate-wide strategic planning systems within large, diversified firms. This article discusses the implementation of such systems on the basis of 3 years of clinical and small sample research. A ‘basic model’ of implementation is used as a basis for comparison to progressive practice as observed in a sample of 13 firms. Furthermore, a new conceptual perspective for the portfolio concept is developed as a complement to the observed approach to implementation.     

Integrated Analysis: Combining Risk and Economic Assessments While Preserving the Separation of Powers

This article presents a process for an integrated policy analysis that combines risk assessment and benefit-cost analysis. This concept, which explicitly combines the two types of related analyses, seems to contradict the long-accepted risk analysis paradigm of separating risk assessment and risk management since benefit-cost analysis is generally considered to be a part of risk management. Yet that separation has become a problem because benefit-cost analysis uses risk assessment results as a starting point and considerable debate over the last several years focused on the incompatibility of the use of upper bounds or "safe" point estimates in many risk assessments with benefit-cost analysis. The problem with these risk assessments is that they ignore probabilistic information. As advanced probabilistic techniques for risk assessment emerge and economic analysts receive distributions of risks instead of point estimates, the artificial separation between risk analysts and the economic/decision analysts complicates the overall analysis. In addition, recent developments in countervailing risk theory suggest that combining the risk and benefit-cost analyses is required to fully understand the complexity of choices and tradeoffs faced by the decisionmaker. This article also argues that the separation of analysis and management is important, but that benefit-cost analysis has been wrongly classified into the risk management category and that the analytical effort associated with understanding the economic impacts of risk reduction actions need to be part of a broader risk assessment process.