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.     

Correspondence analysis used complementary to loglinear analysis

Loglinear analysis and correspondence analysis provide us with two different methods for the decomposition of contingency tables. In this paper we will show that there are cases in which these two techniques can be used complementary to each other. More specifically, we will show that often correspondence analysis can be viewed as providing a decomposition of the difference between two matrices, each following a specific loglinear model. Therefore, in these cases the correspondence analysis solution can be interpreted in terms of the difference between these loglinear models. A generalization of correspondence analysis, recently proposed by Escofier, will also be discussed. With this decomposition, which includes classical correspondence analysis as a special case, it is possible to use correspondence analysis complementary to loglinear analysis in more instances than those described for classical correspondence analysis. In this context correspondence analysis is used for the decomposition of the residuals of specific restricted loglinear models.     

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.