A Nonlinear Structural Equation Mixture Modeling Approach for Nonnormally Distributed Latent Predictor Variables

Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we describe a nonlinear structural equation mixture approach that integrates the strength of parametric approaches (specification of the nonlinear functional relationship) and the flexibility of semiparametric structural equation mixture approaches for approximating the nonnormality of latent predictor variables. In a comparative simulation study, the advantages of the proposed mixture procedure over contemporary approaches [Latent Moderated Structural Equations approach (LMS) and the extended unconstrained approach] are shown for varying degrees of skewness of the latent predictor variables. Whereas the conventional approaches show either biased parameter estimates or standard errors of the nonlinear effects, the proposed mixture approach provides unbiased estimates and standard errors. We present an empirical example from educational research. Guidelines for applications of the approaches and limitations are discussed.     

On the Performance of Likelihood-Based Difference Tests in Nonlinear Structural Equation Models

This article investigates likelihood-based difference statistics for testing nonlinear effects in structural equation modeling using the latent moderated structural equations (LMS) approach. In addition to the standard difference statistic T_D, 2 robust statistics have been developed in the literature to ensure valid results under the conditions of nonnormality or small sample sizes: the robust T_DR and the “strictly positive” T_DRP. These robust statistics have not been examined in combination with LMS yet. In 2 Monte Carlo studies we investigate the performance of these methods for testing quadratic or interaction effects subject to different sources of nonnormality, nonnormality due to the nonlinear terms, and nonnormality due to the distribution of the predictor variables. The results indicate that T_D is preferable to both T_DR and T_DRP. Under the condition of strong nonlinear effects and nonnormal predictors, T_DR often produced negative differences and T_DRP showed no desirable power.     

Perspectives of information and communication technologies for engineering education

The information and communication technologies of today and tomorrow are characterized by: the Internet and its related technological networks; mobile telecommunication systems; video-based multimedia application for communication and information; and speech recognition/automated speech output. They are developing into embedded systems with invisible PC-free interfaces and into new breeds of robots and Multi-Agent Systems. These systems have started to change the technical and organizational structure of all human-machine-systems and their control tasks. In this paper, some aspects of these changes are described in view of the future roles of engineers within society. The paper is based on the memorandum which was drafted by an international expert group to be presented at the Congress on Information and Communication during the First World Engineers' Convention, 19-21 June 2000, Hannover, Germany. Subsequently this memorandum was discussed and agreed on by the participants of the Congress workshops. These participants were several hundred engineers from all over the world. Their ideas and concepts have been integrated into this paper.     

Habitus, social fields, and circuits in rural science education

Schooling and science education are embedded within larger socio-cultural, political and economic contexts, influenced by global flows of capital, labor, ideas, and images. In this article we consider the ways in which ethnography traces the web of interactions (circuits), in a rural community and the ways that science inquiry was associated with character education. Our discussion examines the relationship between social fields, habitus, and meritocracy under new and ever-changing neoliberal conditions. These macro-level forces play out in everyday practices in the community and reveal schools, as well as science education, as sites for struggle.