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.     

Electromagnetic articulography: use of alternating magnetic fields for tracking movements of multiple points inside and outside the vocal tract

The purpose of this paper is to present a new electromagnetic device which uses alternating magnetic fields for tracking movements of multiple points inside and outside the vocal tract. It is biologically safe, noninvasive, it does not interfere with speech movements, allows for multiple recording in the same subject, and for easy collection of large amounts of data. It is especially suitable for evaluation of patients with speech motor impairments.     

Lay conceptions of personality: Eliciting tiers of a scientific conception of personality

Two studies are reported which examine the availability of scientific propositions of personality in lay conceptions of personality. It is argued from a social constructivist perspective that models of personality must derive from and refer to lay conceptions of persons. Eysenck's trait-type model of introversion-extraversion, containing specific propositions about phenotypic and genotypic differences between extraverts and introverts, was utilized as the scientific model of personality and its availability in lay conceptions of personality was examined in two studies. In the first study, subjects were presented with a genotypic characterization of either an introvert or an extravert target person and asked to infer corresponding phenotypic differences. In the second study, the inference process was reversed with subjects being asked to infer genotypic characteristics of introverts versus extraverts on the basis of phenotypic target person desecrations of the two types. Results from both studies show a high degree of accuracy in subjects' inferences, suggesting that laypersons have well-formed conceptions about personality containing ‘higher-order’ psychogenetic propositions corresponding to Eysenck's trait-type model. The implications of the findings for theory construction are discussed.     

Social structure features in three inbred strains of mice, C57Bl/6J, Balb/cj, and NIH: a comparative study

Some features of social living were investigated in three inbred strains of mice: C57Bl/6j, Balb/cj, and NIH. Five social behaviors--Aggression, Submission, Allogrooming, Social Rest and Rest Alone, as well as Wheel Running Activity--were recorded 2 h daily for a week, in 26 groups of seven male mice living in an enriched environment. Dominants and subordinates among strains shared some behavioral characteristics, but strain contributions upon social structure were also detected. Similarities among strains included the appearance of a single dominant mouse per group rated as the most aggressive, besides from being the animal presented with most Submissions. Allogrooming was more frequent among subordinates than among dominants and subordinates. Differences among strains were that agonistic behavior among subordinates was higher in the Balb/cj and NIH groups than in the C57Bl/6j mice. NIH mice were recorded in Rest Alone more often than mice from the other strains. C57Bl/6j dominants showed higher rates of Wheel Running Activity than subordinates.     

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.     

Maps between some different kinds of contraction function: The finite case

In some recent papers, the authors and Peter Gärdenfors have defined and studied two different kinds of formal operation, conceived as possible representations of the intuitive process of contracting a theory to eliminate a proposition. These are partial meet contraction (including as limiting cases full meet contraction and maxichoice contraction) and safe contraction. It is known, via the representation theorem for the former, that every safe contraction operation over a theory is a partial meet contraction over that theory. The purpose of the present paper is to study the relationship more finely, by seeking an explicit map between the component orderings involved in each of the two kinds of contraction. It is shown that at least in the finite case a suitable map exists, with the consequence that the relational, transitively relational, and antisymmetrically relational partial meet contraction functions form identifiable subclasses of the safe contraction functions, over any theory finite modulo logical equivalence. In the process of constructing the map, as the composition of four simple transformations, mediating notions of bottom and top contraction are introduced. The study of the infinite case remains open.     

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.     

Value-based adoption of augmented reality: A study on the influence on online purchase intention in retail

The increasing use of digital technology-based retail services provides new opportunities for digital marketing. In this paper, we investigate how augmented reality (AR) technology can be leveraged as part of the firm's strategy. We explore the online purchase intention through AR smart glasses (ARSG), considering consumers' value assessment through a cost–benefit analysis and the influence of technical, experiential and social AR value drivers. We develop an augmented value-based adoption model addressing four main objectives: (1) Evaluate the effect of the perceived value of ARSG, (2) Evaluate the effect of immersion (experiential dimension), (3) Evaluate the effect of AR devices and technical complexity (technical dimension) and (4) Evaluate the importance of subjective norms (social dimension) on the online purchase intention through AR technology. Based on an ESIC Tech Lab experiment with two types of ARSG from market leaders and AR retail apps, the study uses survey data from 253 participants. The results suggest that the technical dimension has an ambiguous effect, with tech-complexity enhancing directly the perceived value of ARSG for online purchase while reducing the net value of consumers' economic cost–benefit analysis. We find strong evidence that the experiential and social AR dimensions (in the form of immersion and subjective norm) have a significant positive influence on consumers' purchase intention online, which are better predictors than the pure economic cost–benefit assessment (through usefulness and difficulty). Furthermore, the technical innovativeness of consumers is found to increase directly the online purchase intention through ARSG.