Essay: The Role of Participatory Listening in Collaborative Discourse: Insights from Studies of Engineering Design Teams

In this article, we summarize evidence from observations of engineering teams for the importance of active listening in collaborative design problem solving. We focus on the way speakers use freehand sketching to convey complex design ideas, and how listeners support them whilst they do this. We argue that listeners temporarily redistribute the shared cognitive load of discourse production and comprehension within design teams: whilst speakers are engaged in sketch construction they are unable to take account of listener understanding, and listeners respond intuitively by anticipating and avoiding difficulties in this process. We conclude that this cooperativeness emerges naturally from the operation of effort conserving principles underlying collaborative social interaction, and show that by focusing on the contribution of the listener to the production of creative engineering discourse, this principle can be thrown into sharp relief.     

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.     

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.     

Book Reviews

There is a lack of research investigating Pacific peoples' gambling within a New Zealand context. In this paper, data about gambling activity (rather than problem gambling) are presented from the first data collection point for a cohort of mothers who are part of the longitudinal Pacific Islands Families study. The results indicate that gambling behaviour could be influenced by cultural differences. For example, Tongans are more likely to gamble than Samoans, and those who undertake traditional gift giving customs are likely to spend more money on gambling than those who do not. This paper identifies a need for research on Pacific peoples' gambling to acknowledge ethnic-specific cultural influences on gambling practices.     

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.     

Estimation of a discriminant function from a mixture of two inverse Weibull distributions

The classification of a random variable based on a mixture can be meaningfully discussed only if the class of all finite mixtures is identifiable. In this paper, we find the maximum-likelihood estimates of the parameters of the mixture of two inverse Weibull distributions by using classified and unclassified observations. Next, we estimate the nonlinear discriminant function of the underlying model. Also, we calculate the total probabilities of misclassification as well as the percentage bias. In addition, we investigate the performance of all results through a series of simulation experiments by means of relative efficiencies. Finally, we analyse some simulated and real data sets through the findings of the paper.     

RELIGIOUS REFERENCE GROUPS AND THE PERSISTENCE OF NORMATIVE BEHAVIOR: AN EMPIRICAL TEST

Reference groups and significant others are vitally important in both the formation and the persistence or change of normative as well as deviant behavior patterns. Thus one's initial religious beliefs and behavior (or lack thereof) reflect the socializing influence of the family. However, the situation may change when young people leave home for education or work, as demonstrated by research that shows decreases in religious beliefs or church attendance when young people leave home to attend college. In contrast to the pattern whereby religiosity declines in a college or university environment, we maintain that students who develop close ties with others who are religious, especially in a highly religious community, will maintain the same patterns of high commitment developed in their families. Specifically, we hypothesize that religious beliefs and participation will be positively related to (1) parents' religious beliefs and practices and (2) current friends' religious beliefs and participation. These hypotheses were tested with a sample of college students living on campus (n = 339). The data support the argument that students' current religious beliefs and behavior are related to both their parents' religiosity and the reinforcing effects of the religiosity of their current friends.