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.     

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.     

Sheldon Smith on Newton’s Derivative: Retrospective Assignation,Externalism and the History of Mathematics

To illustrate the view that a speaker can have a partial understanding of a concept, Burge uses the example of Leibniz’s and Newton’s understanding of the concept of derivative. In a recent article, Sheldon Smith criticizes this example and maintains that Newton’s and Leibniz’s use of their derivative symbols does not univocally determine their references. The present article aims at challenging Smith’s analysis. It first shows that Smith misconstrues Burge’s position. It second suggests that the philosophical lessons one should draw from the practice of the historians of philosophy are more ambivalent than what Smith thinks.

     

Llamas use social information from conspecifics and humans to solve a spatial detour task

Animal Cognition - Learning by observing others (i.e. social learning) is an important mechanism to reduce the costs of individual learning. Social learning can occur between conspecifics but also...     

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.     

Pain in the eye of the beholder: Variations in pain visual representations as a function of face ethnicity and culture

Pain experienced by Black individuals is systematically underestimated, and recent studies have shown that part of this bias is rooted in perceptual factors. We used Reverse Correlation to estimate visual representations of the pain expression in Black and White faces, in participants originating from both Western and African countries. Groups of raters were then asked to evaluate the presence of pain and other emotions in these representations. A second group of White raters then evaluated those same representations placed over a neutral background face (50% White; 50% Black). Image-based analyses show significant effects of culture and face ethnicity, but no interaction between the two factors. Western representations were more likely to be judged as expressing pain than African representations. For both cultural groups, raters also perceived more pain in White face representations than in Black face representations. However, when changing the background stimulus to the neutral background face, this effect of face ethnic profile disappeared. Overall, these results suggest that individuals have different expectations of how pain is expressed by Black and White individuals, and that cultural factors may explain a part of this phenomenon