Fitting multivariage normal finite mixtures subject to structural equation modeling

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the differences between the components in the mixture. Within the general model, individual parameters can be subjected to equality, nonlinear and simple bounds constraints. Confidence intervals are based on the inverse of the Hessian and on the likelihood profile. Several illustrations are given and results of a simulation study concerning the confidence intervals are reported.     

The Incarcerated Female Felon and Substance Abuse: Demographics,Needs Assessment,and Program Planning for a Neglected Population

Incarcerated women (203 of 237) completed a needs survey designed by an inmate steering committee. The typical inmate was a European American mother of 2 children. Relevant programming (substance abuse education classes, self-study programs, didactic groups and workshops) is discussed.     

Personality characteristics of successful applicants to the priesthood

This study investigated personality characteristics of successful pastoral candidates to a major Catholic religious order. Personality measures (i.e., MMPI-2 and 16PF) were administered to 21 male applicants between 1990 and 1994 who subsequently entered into religious life. Results suggest that these clergy applicants were generally well-adjusted, socially responsible, and interpersonally sensitive. However, results also suggest a tendency for defensiveness. Coping with perceived negative impulses (i.e., anger and hostility) may also be an issue for many. Implications for future research are offered.     

New Concepts in the 2014 ACA Code of Ethics

The 2014 revision of the ACA Code of Ethics (American Counseling Association [ACA], 2014 ) substantially raises the bar for the ethical practice of professional counselors. This article provides interviews with members of the ACA Ethics Revision Task Force that explore and clarify new imperatives in the areas of ethical decision making, professional values, managing and maintaining boundaries, technology (including social media), the nonimposition of counselor personal values, counselor education, legal issues, sliding scales, and fee splitting.     

A framework for ML estimation of parameters of (mixtures of) common reaction time distributions given optional truncation or censoring

We present a framework for distributional reaction time (RT) analysis, based on maximum likelihood (ML) estimation. Given certain information relating to chosen distribution functions, one can estimate the parameters of these distributions and of finite mixtures of these distributions. In addition, left and/or right censoring or truncation may be imposed. Censoring and truncation are useful methods by which to accommodate outlying observations, which are a pervasive problem in RT research. We consider five RT distributions: the Weibull, the ex-Gaussian, the gamma, the log-normal, and the Wald. We employ quasi-Newton optimization to obtain ML estimates. Multicase distributional analyses can be carried out, which enable one to conduct detailed (across or within subjects) comparisons of RT data by means of loglikelihood difference tests. Parameters may be freely estimated, estimated subject to boundary constraints, constrained to be equal (within or over cases), or fixed. To demonstrate the feasibility of ML estimation and to illustrate some of the possibilities offered by the present approach, we present three small simulation studies. In addition, we present three illustrative analyses of real data.     

EZ does it! Extensions of the EZ-diffusion model

In this rejoinder, we address two of Ratcliff’s main concerns with respect to the EZ-diffusion model (Ratcliff, 2008). First, we introduce “robust-EZ,” a mixture model approach to achieve robustness against the presence of response contaminants that might otherwise distort parameter estimates. Second, we discuss an extension of the EZ model that allows the estimation of starting point as an additional parameter. Together with recently developed, user-friendly software programs for fitting the full diffusion model (Vandekerckhove & Tuerlinckx, 2007; Voss & Voss, 2007), the development of the EZ model and its extensions is part of a larger effort to make diffusion model analyses accessible to a broader audience, an effort that is long overdue.     

Uncertainty Management and Social Issues: Uncertainty as an Important Determinant of Reactions to Socially Deviating People1

In this paper, the social psychology of uncertainty management is used to explain reactions to socially deviating people. In Study 1, we examine how people react to a person communicating negative messages about their home country; in Study 2, how a representative sample of the Dutch society reacts to encounters with a homeless person; and in Study 3, what the behavioral and psychological reactions are of people in an anticipated interaction with a homeless individual. All 3 studies reveal that personal uncertainty—whether made salient in a subtle manner or measured by means of individual differences in the extent to which uncertainty is considered an emotionally threatening experience—is an important determinant of reactions to socially deviating persons.

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The effects of time pressure on chess skill: an investigation into fast and slow processes underlying expert performance

The ability to play chess is generally assumed to depend on two types of processes: slow processes such as search, and fast processes such as pattern recognition. It has been argued that an increase in time pressure during a game selectively hinders the ability to engage in slow processes. Here we study the effect of time pressure on expert chess performance in order to test the hypothesis that compared to weak players, strong players depend relatively heavily on fast processes. In the first study we examine the performance of players of various strengths at an online chess server, for games played under different time controls. In a second study we examine the effect of time controls on performance in world championship matches. Both studies consistently show that skill differences between players become less predictive of the game outcome as the time controls are tightened. This result indicates that slow processes are at least as important for strong players as they are for weak players. Our findings pose a challenge for current theorizing in the field of expertise and chess.