Measurement and structure of pathological gambling behavior

The serious effects of pathological gambling on both gamblers and their families warrants research on the disorder. This study aimed at identifying components of pathological gambling with the goal of developing methods for early detection and preventive strategies. A factor analysis of behaviors hypothesized to relate to pathological gambling resulted in a multidimensional model of the disorder. Eight factors were identified, including distinct neurotic, psychopathic, and impulsive components, and used in a comparative analysis of 83 admitted compulsive gamblers and 61 nongamblers. Five of the factors differentiated the two groups even when sex, age, and education were controlled. Implications of these findings are discussed.     

Amount of information about the attitude object and attitude-behavior consistency

The synthesis of two separate lines of inquiry--research on information integration and longitudinal studies of attitudes--prompted the hypothesis that the degree of consistency between attitudes and behavior will increase as a function of the amount of information available about the attitude object. The hypothesis was tested in three separate longitudinal studies, ranging in length from 4 days to 4 months, that investigated the following behaviors: voting for candidates for political office, voting for two social policy election initiatives, and having an influenza vaccination. In support of the hypothesis, in each study, amount of information moderated the consistency between attitudes and behavior; and the significance of this relation remained even after controlling for the effects of a number of other potential moderators, including prior direct behavioral experience with the attitude object and attitude certainty. Consistent with previous research, direct behavioral experience was also a determinant of attitude-behavior consistency, and for the behavior of having an influenza vaccination, this relation was independent of the effect of amount of information. The discussion focuses on the interrelation among moderators of attitude-behavior consistency and on the theoretical implications of the findings.     

Type A behavior pattern and the judgment of noncontingency: mediating roles of mood and perspective

Past research indicates that Type A's and B's differ in their behavioral responses to lack of control. The present study examined perceptual judgments of noncontingency in an attempt to clarify further the role of a control dynamic in Type A-B differences. Type A's and B's assumed the role of either an actor or an observer on a standard contingency judgment task. Consistent with previous research, both Type A's and B's exhibited an illusion of control when in the role of actor. Only Type B's exhibited an illusion of control when observing another person perform the task. Additional analyses indicated that the absence of an illusion of control by Type A observers reflected accuracy rather than a motivational distortion. Mood was also found to mediate control judgments, but only for actors. The plausibility of a memory-based interpretation for the mood effects is discussed.     

Three-way metric unfolding via alternating weighted least squares

Three-way unfolding was developed by DeSarbo (1978) and reported in DeSarbo and Carroll (1980, 1981) as a new model to accommodate the analysis of two-mode three-way data (e.g., nonsymmetric proximities for stimulus objects collected over time) and three-mode, three-way data (e.g., subjects rendering preference judgments for various stimuli in different usage occasions or situations). This paper presents a revised objective function and new algorithm which attempt to prevent the common type of degenerate solutions encountered in typical unfolding analysis. We begin with an introduction of the problem and a review of three-way unfolding. The three-way unfolding model, weighted objective function, and new algorithm are presented. Monte Carlo work via a fractional factorial experimental design is described investigating the effect of several data and model factors on overall algorithm performance. Finally, three applications of the methodology are reported illustrating the flexibility and robustness of the procedure.We wish to thank the editor and reviewers for their insightful comments.     

Combinatorial data analysis: Association and partial association

A combinatorial data analysis strategy is reviewed that is designed to compare two arbitrary measures of proximity defined between the objects from some set. Based on a particular cross-product definition of correspondence between these two numerically specified notions of proximity (typically represented in the form of matrices), extensions are then pursued to indices of partial association that relate the observed pattern of correspondence between the first two proximity measures to a third. The attendant issues of index normalization and significance testing are discussed; the latter is approached through a simple randomization model implemented either through a Monte Carlo procedure or distributional approximations based on the first three moments. Applications of the original comparison strategy and its extensions to partial association may be developed for a variety of methodological and substantive tasks. Besides rank correlation, we emphasize the topics of spatial autocorrelation for one variable and spatial association between two and mention the connection to the usual randomization approach for one-way analysis-of-variance.     

Statistical consistency and hypothesis testing for nonmetric multidimensional scaling

The properties of nonmetric multidimensional scaling (NMDS) are explored by specifying statistical models, proving statistical consistency, and developing hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. For these models, statistical consistency often depends crucially upon how error enters the model and how data are collected and summarized (e.g., by means, medians, or rank statistics). A maximum likelihood estimator for NMDS is developed, and its relationship to the standard Shepard-Kruskal estimation method is described. This maximum likelihood framework is used to develop a method for testing the overall fit of the model.     

Identification with another person: Manipulated by means of subliminal stimulation

Studied problems of identification, using a meta-contrast design. The first stimulus (A) was always the word ME. In experiment 1 , the second stimulus (B) depicted an aggressor and a victim facing each other. The subliminal A was flashed either on the victim or the aggressor or completely withheld. In experiment 2 , B showed two persons standing against different backgrounds: an open horizon or a closed room. It was assumed that the subject would be "forced" to identify with that figure in B on which A was flashed. Subjects in experiment 1 were 18 psychiatric patients and in experiment 2 , 32 professional artists. The results showed that the subliminal manipulation had been effective: e.g., when led by A to identify with the aggressor, projective-sensitive and borderline subjects were confused and even reported perceptual difficulties; when led to identify with the open side, highly creative artists, as opposed to less creative ones, reported more positive impressions of the B theme.