A Critical Look at Some Analyses of Major League Baseball Salaries

At a data analysis exposition sponsored by the Section on Statistical Graphics of the ASA in 1988, 15 groups of statisticians analyzed the same data about salaries of major league baseball players. By examining what they did, what worked, and what failed, we can begin to learn about the relative strengths and weaknesses of different approaches to analyzing data. The data are rich in difficulties. They require reexpression, contain errors and outliers, and exhibit nonlinear relationships. They thus pose a realistic challenge to the variety of data analysis techniques used. The analysis groups chose a wide range of model-fitting methods, including regression, principal components, factor analysis, time series, and CART. We thus have an effective framework for comparing these approaches so that we can learn more about them. Our examination shows that approaches commonly identified with Exploratory Data Analysis are substantially more effective at revealing the underlying patterns in the data and at building parsimonious, understandable models that fit the data well. We also find that common data displays, when applied carefully, are often sufficient for even complex analyses such as this.     

Jensen's Inequality for General Location Parameter

A wide class of location parameters is shown to satisfy Jensen's inequality. When the expectation EX exists and l is a convex function, Jensen's inequality states that El(x) ≥ l(EX). It is shown that for μ, a properly defined location parameter, μ(l(x)) μ l(μ(x)).     

Density estimation using asymmetric kernels and Bayes bandwidths with censored data

We propose a modification to the regular kernel density estimation method that use asymmetric kernels to circumvent the spill over problem for densities with positive support. First a pivoting method is introduced for placement of the data relative to the kernel function. This yields a strongly consistent density estimator that integrates to one for each fixed bandwidth in contrast to most density estimators based on asymmetric kernels proposed in the literature. Then a data-driven Bayesian local bandwidth selection method is presented and lognormal, gamma, Weibull and inverse Gaussian kernels are discussed as useful special cases. Simulation results and a real-data example illustrate the advantages of the new methodology.     

Double‐mouthed discourse: Interpreting,framing, and participant roles1

In this article I examine multilingual displays in a Congolese Pentecostal church in Cape Town, South Africa. I focus on the simultaneous interpreting of the pastor's French sermon into English. I argue that the interpreting activity performed at church is used as a powerful interactional device to dramatize and shape the pastor's sermon. A close examination of participant roles shows that although these may appear to be predetermined by the interpretee‐interpreter format of the sermon, speaking roles are actually fluid and negotiated. I submit that an important role of the church interpreter is to convey the pastor's inspiration from the Holy Spirit and reach out to the potential audience absent from the here and now of the service. His high emotional engagement helps convey this inspiration prospectively to the audience and retroactively to the pastor himself.     

Comparing several experimental groups with a control in the multivariate case

This paper presents a multivariate extension of Dunnett's test for comparing simultaneously k treatment group means with a single control group mean. A test based on Hotelling T²statistics is presented and approximate critical values are evaluated for the case of equal numbers of observations in each group, for the .05 and .01 levels of significance, for 1 to 5 variates, for 1 to 10 treatment groups, and for varying degrees of freedom. The accuracy of the procedure for generating approximate critical values is assessed via simulation studies conducted for selected cases and an example is presented using real data.     

Mapping Invasive Species Risks with Stochastic Models: A Cross-Border United States-Canada Application for Sirex noctilio Fabricius

Nonindigenous species have caused significant impacts to North American forests despite past and present international phytosanitary efforts. Though broadly acknowledged, the risks of pest invasions are difficult to quantify as they involve interactions between many factors that operate across a range of spatial and temporal scales: the transmission of invading organisms via various pathways, their spread and establishment in new environments. Our study presents a stochastic simulation approach to quantify these risks and associated uncertainties through time in a unified fashion. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. We simulate new potential entries of S. noctilio as a stochastic process, based on recent volumes of marine shipments of commodities from countries where S. noctilio is established, as well as the broad dynamics of foreign marine imports. The results are then linked with a spatial model that simulates the spread of S. noctilio within the geographical distribution of its hosts (pines) while incorporating existing knowledge about its behavior in North American landscapes. Through replications, this approach yields a spatial representation of S. noctilio risks and uncertainties in a single integrated product. The approach should also be appealing to decisionmakers, since it accounts for projected flows of commodities that may serve as conduits for pest entry. Our 30-year forecasts indicate high establishment probability in Ontario, Quebec, and the northeastern United States, but further southward expansion of S. noctilio is uncertain, ultimately depending on the impact of recent international treatment standards for wood packing materials.     

The complementarity of internal integration and product modularity: An empirical study of their interaction effect on competitive capabilities

Modular product design and internal integration are commonly adopted by manufacturers to improve operational performance. A number of studies argue that the adoption of product modularity significantly alters organization design, which affects the impact of internal integration on competitive capabilities. This paper thus aims to empirically explore the individual effects as well as interaction effects of product modularity and internal integration on competitive capabilities. The competitive capabilities studied in this paper include product innovativeness, low price, product quality, delivery, flexibility and customer services. After analysing the data from 251 Hong Kong manufacturers through moderated multiple regression analysis, the study found that better internal integration can significantly improve product innovativeness, product quality, delivery, flexibility and customer services, while a high level of product modularity enhances product innovativeness, flexibility and customer services. More importantly, the study shows that internal integration and product modularity can interact to improve product innovativeness and product quality. These results enhance our understanding of the interaction of product design and organizational coordination.     

Teacher–Child Relationships from Kindergarten to Sixth Grade: Early Childhood Predictors of Teacher-perceived Conflict and Closeness

This article examined general trends in teacher-reported conflict and closeness among 878 children from kindergarten through sixth grade, and examined early childhood characteristics that predict differences in initial levels and growth of conflict and closeness over time. Results indicated modest stability of teacher-perceived conflict and closeness through sixth grade, with relatively greater stability in perceptions of conflict. Levels of conflict at kindergarten were higher for children who were male, Black, had greater mean hours of childcare, had lower academic achievement scores, and had greater externalizing behavior. Children identified as Black and those with less sensitive mothers were at greater risk for increased conflict with teachers over time. Levels of teacher-reported closeness were lower when children were male, had lower quality home environments, and had lower academic achievement scores. The gap in closeness ratings between males and females increased in the middle elementary school years. Additional analyses were conduced to explore differences in teacher ratings of conflict between Black and White students.     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.