with rapid economic development and industrialization, the construction industry continues to rank among the most hazardous industries in the world. therefore, construction safety is always a significant concern for both practitioners and researchers. the objective of this study was to create a structural modeling of components that influence the safety performance in construction projects.we f...

Structural equation modeling (SEM) is an important statistical tool for evaluating complex relations in several research areas. In epidemiology, the use and discussion of SEM have been limited thus far. This article presents basic principles and concepts in SEM, including an application using epidemiological data analysis from a study on the determinants of cognitive development in young childr...

We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the biva...

To complement recent articles in this journal on structural equation modeling (SEM) practice and principles by Martens and by Quintana and Maxwell, respectively, the authors offer a consumer’s guide to SEM. Using an example derived from theory and research on vocational psychology, the authors outline six steps in SEM: model specification, identification, data preparation and screening, estimat...

Structural equation modeling (SEM) provides a dependable framework for testing differences among groups on latent variables (constructs, factors). The purpose of this article is to illustrate SEM-based testing for group mean differences on latent variables. Related procedures of confirmatory factor analysis and testing for measurement invariance across compared groups are also presented in the ...

Due to its flexibility and self-determination, Self-organized learning neural network has been widely applied in many fields; meanwhile, it has a well trend to develop. Structural equation model (SEM) may be reconstructed into a self-organized learning neural network, but the algorithm of SEM need to be improved. In this paper, we first present an improved partial least square (PLS) algorithm i...

Linear stochastic differential equations (SDE) are expressed as an exact discrete model (EDM) and estimated with structural equation models (SEM) and the Kalman filter (KF) algorithm. The SEM likelihood is well defined even for the times series case and the SEM and KF approach yield the same likelihood. The oversampling approach is introduced in order to formulate the EDM on a time grid which i...

Well-being has been given special emphasis in quality of life. It involves living a meaningful, life satisfaction, stability and happiness in life. Well-being also concerns the satisfaction of physical, psychological, social needs and demands of an individual. The purpose of this study was to validate three-factor measurement model of well-being using structural equation modeling (SEM). The con...

This article summarizes the proceedings of a symposium presented at the 2005 Research Society on Alcoholism meeting in Santa Barbara, California. This symposium begins with a description by Michael Windle of structural equation modeling (SEM), including the assets and liabilities of this approach. Next, Marc Schuckit and Tom Smith demonstrate the application of an SEM approach to understanding ...