Visual perception of surface curvature: psychophysics of curvature detection induced by motion parallax

The continuous approach to optic-flow processing shows that the curvature of a moving surface is related to a second spatial derivative of the velocity field, the spin variation (Droulez & Cornilleau-Pérès, 1989). With this approach as a theoretical framework, visual sensitivity to the curvature of a cylinder in motion was measured using a task of discrimination between cylindrical and planar patches. The results confirm the predictions suggested by the theory: (1) Sensitivity to curvature was always greater when the cylinder axis and the frontal translation were parallel than when they were orthogonal. The ratio of curvature detection thresholds in the two cases was between 1.3 and 2.5; the value predicted from the spin variation theory is about 2. (2) Sensitivity to curvature increased strongly with the velocity of the motion but was only weakly affected by its amplitude and the duration of viewing for the range of values used in our experiments.     

Using item-specific instructional information in achievement modeling

The problem of detecting instructional sensitivity (item basis) in test items is considered. An illustration is given which shows that for tests with many biased items, traditional item bias detection schemes give a very poor assessment of bias. A new method is proposed instead. This method extends item response theory (IRT) by including item-specific auxiliary measurement information related to opportunity-to-learn. Item-specific variation in measurement relations across students with varying opportunity-to-learn is allowed for.This paper was presented at the 1987 AERA meeting in Washington, DC. This research was supported by grant OERI-G-86-003 from the Office of Educational Research and Improvement, Department of Education. The author thanks Michael Hollis and Chih-fen Kao for valuable research assistance, and appreciates valuable comments made by an anonymous reviewer.     

Factor structure in groups selected on observed scores

A new method is proposed for estimating factor means and factor covariances in a group of individuals selected on their observed scores. The selection variable is, for example, the total score on an admissions test. Given a factor model for the test items based on the group of test takers, we may be interested in the factor structure for those in the top quartile. The differences in factor means and covariances between this selected group and the full group gives useful information both on successful test performance and on test validity. The new method draws on the classic Pearson-Lawley selection formulas. It avoids the fallacy of factor analysis on the selected group, which would lead to incorrect estimates. The new method is applied to a simple factor structure model for the GMAT test. Although the majority of the GMAT items test verbal skills, it is found that a quantitative factor shows the greatest change in moving from average to top quartile test takers.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.     

Three-dimensional perspective drawing of two-dimensional functions with microcomputers

In this paper, we present a BASIC program for Apple II series computers that allows the user to obtain perspective drawings of two-dimensional functions of known analytical expression. Also, we outline a procedure for obtaining perspective representations of two-dimensional arrays of data using the same program. The program should run on any computer with graphics mode with only slight modifications in the graphics commands.     

Beliefs about and experiences with battering: Women and men in two populations

A questionnaire was developed to measure beliefs about and experiences with violence in the family. Two groups of persons in two different states who had attended conferences on battered women participated in this research. Of the 177 subjects (84% women, 16% men), none of the men had been battered, yet over one-third of the women had been; more older women reported having been adult battering victims than did younger women; the women had less formal education than the men; the women in the lower educational groups were more likely to have been battered and to report fear of becoming victims; and the social service workers reported little fear of battering.     

A general structural equation model with dichotomous,ordered categorical,and continuous latent variable indicators

A structural equation model is proposed with a generalized measurement part, allowing for dichotomous and ordered categorical variables (indicators) in addition to continuous ones. A computationally feasible three-stage estimator is proposed for any combination of observed variable types. This approach provides large-sample chi-square tests of fit and standard errors of estimates for situations not previously covered. Two multiple-indicator modeling examples are given. One is a simultaneous analysis of two groups with a structural equation model underlying skewed Likert variables. The second is a longitudinal model with a structural model for multivariate probit regressions.This research was supported by Grant No. 81-IJ-CX-0015 from the National Institute of Justice, by Grant No. DA 01070 from the U.S. Public Health Service, and by Grant No. SES-8312583 from the National Science Foundation. I thank Julie Honig for drawing the figures. Requests for reprints should be sent to Bengt Muthén, Graduate School of Education, University of California, Los Angeles, California 90024.     

Perception of structure in novel music

Two experiments demonstrated the way in which musicians and nonmusicians process realistic music encountered for the first time. A set of tunes whose members were related to each other by a number of specific musical relationships was constructed. In Experiment 1, subjects gave similarity judgments of all pairs of tunes, which were analyzed by the ADDTREE clustering program. Musicians and nonmusicians gave essentially equivalent results: Tunes with different rhythms were rated as being very dissimilar, whereas tunes identical except for being in a major versus a minor mode were rated as being highly similar. In Experiment 2, subjects learned to identify the tunes, and their errors formed a confusion matrix. The matrix was submitted to a clustering analysis. Results from the two experiments corresponded better for the nonmusicians than for the musicians. Musicians presumably exceed nonmusicians in the ability to categorize music in multiple ways, but even nonmusicians extract considerable information from newly heard music.     

Effects of family therapy for substance abuse: A systematic review of recent research

One of the most serious psychosocial problems worldwide is substance abuse because of its repercussions not only on the physical and psychological health of the abuser but also on their relational functioning. Among the well-established therapeutic approaches for the treatment of substance abuse is family therapy, which, in addition to influencing personal variables, promotes changes in family dynamics. The main objective of this study is to review the scientific literature published from 2010 to the present on the efficacy and effectiveness shown by family-based treatment approaches for substance use problems both in adolescent and adult samples. In addition, the effect on secondary variables such as family functioning and behavioral problems is evaluated. The empirical evidence accumulated in the last decade and reviewed in the present study indicates that the incorporation of family members in the treatment of substance abuse produces benefits by diminishing consumption and improving family functioning. Limitations of this study and of the research reviewed are discussed and directions for future research are provided.