Khaled Bedair's guest appearances

Khaled Bedair

LISA: Laboratory for Interdisciplinary Statistical Analysis - Short Courses

ERIC SMITH

Matt Williams

Anne Ryan

Block Design

Qing Li

Eric Vance

Jonathan Stallings

Yiming Peng

Mark Seiss

Chris Franck

Nels Johnson

Marcos Carzolio

Liang Shan

Wandi Huang

Sai Wang

OwlTail

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance and multiple linear regression models. This short course features an introduction to the logic of SEM, the assumptions and required input for SEM analysis, and how to perform SEM analyses using the AMOS (Analysis of Moment Structures) software. We also will cover time–related latent variables, the use of modification indices and critical ratio in exploratory analyses, computation of implied moments, factor score weights, total effects, and indirect effects.Course files available here: www.lisa.stat.vt.edu/?q=node/4875.

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance and multiple linear regression models. This short course features an introduction to the logic of SEM, the assumptions and required input for SEM analysis, and how to perform SEM analyses using the AMOS (Analysis of Moment Structures) software. We also will cover time–related latent variables, the use of modification indices and critical ratio in exploratory analyses, computation of implied moments, factor score weights, total effects, and indirect effects.<br><br>Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/4875" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/4875</a>.

Structural Equation Modeling by Khaled Bedair

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance and multiple linear regression models. This short course features an introduction to the logic of SEM, the assumptions and required input for SEM analysis, and how to perform SEM analyses using the AMOS (Analysis of Moment Structures) software. We also will cover time–related latent variables, the use of modification indices and critical ratio in exploratory analyses, computation of implied moments, factor score weights, total effects, and indirect effects.Course files available here: www.lisa.stat.vt.edu/?q=node/2319

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance and multiple linear regression models. This short course features an introduction to the logic of SEM, the assumptions and required input for SEM analysis, and how to perform SEM analyses using the AMOS (Analysis of Moment Structures) software. We also will cover time–related latent variables, the use of modification indices and critical ratio in exploratory analyses, computation of implied moments, factor score weights, total effects, and indirect effects.<br><br>Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/2319" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/2319</a>