Sexual fantasy experiences and guilt among conservative Christians: An exploratory study

This study examines the sexual fantasy experiences and cognitive‐affective evaluations in a sample of conservative Christians. The study also operationalizes and documents fantasy guilt as an entity distinct from the more broadly defined category of sex guilt. Respondents reported normative fantasy categories and frequencies of fantasy occurrences. Concomitantly, fantasy episodes were experienced along with substantial to high levels of guilt over fantasizing. Findings show a complex interrelationship between a subject's cognitions, emotions, and fantasy guilt. These point to the import this sample gives to learned cognitions in furthering guilt, over and above the content or frequency of the fantasy experience itself.     

Changes in At-Risk American Men's Crime and Substance Use Trajectories Following Fatherhood

Fatherhood can be a turning point in development and in men's crime and substance use trajectories. At-risk boys (N = 206) were assessed annually from ages 12 to 31 years. Crime, arrest, and tobacco, alcohol, and marijuana use trajectories were examined. Marriage was associated with lower levels of crime and less frequent substance use. Following the birth of a first biological child, men's crime trajectories showed slope decreases, and tobacco and alcohol use trajectories showed level decreases. The older men were when they became fathers, the greater the level decreases were in crime and alcohol use and the less the slope decreases were in tobacco and marijuana use. Patterns are consistent with theories of social control and social timetables.     

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.     

Inference on effect size indices from several two-armed experiments

The statistical inference problem on effect size indices is addressed using a series of independent two-armed experiments from k arbitrary populations. The effect size parameter simply quantifies the difference between two groups. It is a meaningful index to be used when data are measured on different scales. In the context of bivariate statistical models, we define estimators of the effect size indices and propose large sample testing procedures to test the homogeneity of these indices. The null and non-null distributions of the proposed testing procedures are derived and their performance is evaluated via Monte Carlo simulation. Further, three types of interval estimation of the proposed indices are considered for both combined and uncombined data. Lower and upper confidence limits for the actual effect size indices are obtained and compared via bootstrapping. It is found that the length of the intervals based on the combined effect size estimator are almost half the length of the intervals based on the uncombined effect size estimators. Finally, we illustrate the proposed procedures for hypothesis testing and interval estimation using a real data set.     

Pooled Cross-Sectional and Time Series Data: A Survey of Current Statistical Methodology

A data base that provides a multivariate statistical history for each of a number of individual entities is called a pooled cross-sectional and time series data base in the econometrics literature. In marketing and survey literature the terms panel data or longitudinal data are often used. In management science a convenient term might be management data base. Such a data base provides a particularly rich environment for statistical analysis. This article reviews methods for estimating multivariate relationships particular to each individual entity and for summarizing these relationships for a number of individuals. Inference to a larger population when the data base is viewed as a sample is also considered.     

Understanding Canonical Correlation through the General Linear Model and Principal Components

Canonical correlation has been little used and little understood, even by otherwise sophisticated analysts. An alternative approach to canonical correlation, based on a general linear multivariate model, is presented. Properties of principal component analysis are used to help explain the method. Standard computational methods for full rank canonical correlation, techniques for canonical correlation on component scores, and canonical correlation with less than full rank are discussed. They are seen to be essentially equivalent when the model equation for canonical correlation on component scores is presented. The two approaches to less than full rank situations are equivalent in some senses, but quite different in usefulness, depending on the application. An example dataset is analyzed in detail to help demonstrate the conclusions.     

Accent on Teaching Materials

This department includes the two sections New Developments in Statistical Computing and Statistical Computing Software Reviews; suitable contents for each of these sections are described under the respective section heading. Articles submitted for the department, outside the two sections, should not be highly technical and should be relevant to the teaching or practice of statistical computing.

An unbiased estimator of e is used to motivate a simple simulation exercise that requires only observations from the distribution uniform on (0, 1). Antithetic variables are introduced and applied to the simulation problem to give a second unbiased estimator of e with reduced variance.     

The Security of Gambling and Gambling with Security: A Rejoinder

Social media has become an established tool to engage and maintain customer loyalty. However, its successful use involves a balance between promotion, public relations and corporate social responsibility. Nineteen individuals working in the Australian gambling industry were interviewed. The aim was to explore how gambling operators are using social media to engage with users and promote products, their considerations underpinning these actions, and the extent to which responsible gambling practices are included. All operators were active on social media and used these platforms to attempt to increase customer engagement and strengthen existing relationships. Gambling-related content was usually balanced against non-gambling content, or operators focused exclusively on non-gambling content. Sales goals or raising revenue were not direct aims of social media use. Operators sought to use social media as an indirect way to maintain their customer base and attract new customers via favourable ratings and information transfer. Few operators provided specific responsible gambling messages, despite being mindful of the dangers of targeting vulnerable populations, specifically young people and problem gamblers. This study is unique as it provides an in-depth first-hand account of how gambling operators are using social media.