Noninformative priors for the normal variance ratio

In this paper, we consider noninformative priors for the ratio of variances in two normal populations. We develop first and second order matching priors. We find that the second order matching prior matches alternative coverage probabilities up to the second order and is also a HPD matching prior. It turns out that among the reference priors, only one-at-a-time reference prior satisfies a second order matching criterion. Our simulation study indicates that the one-at-a-time reference prior performs better than other reference priors in terms of matching the target coverage probabilities in a frequentist sense. This work is supported by Korea Research Foundation Grant (KRF-2004-002-C00041).     

Consequences of work force reduction: Some employer and union evidence

Despite the popularity of workforce cutbacks in the 1990s, largescale empirical stud-ies at the bargaining unit level are rare. I explore some of the consequences of per-manent work force reduction using data from both employer and union respondents. About 56 percent of employer participants and 57 percent of local union officials reported a permanent reduction of bargaining unit employees. In comparing bargain-ing units that experienced a permanent reduction of union members, results obtained from both employers and union officials indicated a significant negative impact on over-all employee satisfaction and labor climate. Additional analyses with union respon-dents revealed that the reduction of bargaining unit employees was also associated with a higher rate of grievances and absenteeism and poorer relations between union members and their supervisors.     

Prior distribution assessment for a multivariate normal distribution: an experimental study

A variety of methods of eliciting a prior distribution for a multivariate normal (MVN) distribution have recently been proposed. This paper reports an experiment in which 16 meteorologists used the methods to quantify their opinions about climatology variables. Our results compare prior models and show, in particular, that it can be better to assume the mean and variance of an MVN distribution are independent a priori, rather than to model opinion by the conjugate prior distribution. Using a proper scoring rule, different forms of assessment task are examined and alternative ways of estimating parameters are compared. To quantify opinion about means, it proved preferable to ask directly about the means rather than individual observations while, to quantify opinion about the variance matrix, it was best to ask about deviations from the mean. Further results include recommendations for the way parameters of the prior distribution are estimated.     

Role of Negative Emotion in Communication about CO2 Risks

This article describes how the effectiveness of risk communication is determined by the interaction between emotional and informative elements. An experiment is described that examined the role of negative emotion in communication about CO₂ risks. This experiment was based on the elaboration likelihood model and the related heuristic systematic model of attitude formation. The results indicated that inducing fear of CO₂ risks leads to systematic processing of information about energy conservation as a risk-reducing strategy. In turn, this results in more favorable attitudes toward energy conservation if strong arguments are provided. Individual differences in concern seem to have similar effects.     

Bayesian inference for dynamic social network data

We consider a continuous-time model for the evolution of social networks. A social network is here conceived as a (di-) graph on a set of vertices, representing actors, and the changes of interest are creation and disappearance over time of (arcs) edges in the graph. Hence we model a collection of random edge indicators that are not, in general, independent. We explicitly model the interdependencies between edge indicators that arise from interaction between social entities. A Markov chain is defined in terms of an embedded chain with holding times and transition probabilities. Data are observed at fixed points in time and hence we are not able to observe the embedded chain directly. Introducing a prior distribution for the parameters we may implement an MCMC algorithm for exploring the posterior distribution of the parameters by simulating the evolution of the embedded process between observations.     

NOTE ON POINT AND INTERVAL ESTIMATION AND PREDICTION FOR NORMAL EQUICORRELATED DATA

For normal homoscedastic equicorrelated data the parameters μ, σ and p are identifiable, but it is shown that no consistent estimators exist. Confidence intervals for μ and prediction intervals with known confidence coefficients can, however, be obtained.     

WHO'S PUBLISHING IN JMFT? AN EXAMINATION OF AUTHOR CHARACTERISTICS

This article examines the gender, setting, and degree of the first authors of published articles in JMFT from 1990 to 1995. Findings reveal that men are the first authors of 67% of the articles and women, 33%. PhDs are first authors on 58% of the articles, and authors in university settings write 53% of the published articles. Thirty-nine percent of the articles published during this period were research; 26%, clinical; 16%, theory; and 14%, training. Surprising findings were that MSW authors had a higher acceptance rate than PhDs, and authors in training institutes had a higher acceptance rate than those in university settings.