Dissertation/Thesis Abstract

Structural equation models estimation methods
by Nguyen, Hien D., M.S., California State University, Long Beach, 2015, 108; 1602758
Abstract (Summary)

Structural equation modeling (SEM) is a widely used statistical method in the social and behavioral sciences. In its early days, SEM was restricted to linear models among latent variables. This thesis will illustrate the maximum likelihood method for estimating linear models, the product indicator, the two-step methods, and the mixture method for estimating non-linear models. All examples will be executed through the statistical software R. Additionally, examples of bootstrapping will be shown in the context of SEM for the purpose of comparing different estimation methods, performing power analysis, and determining model fit for small and large sample sizes.

Indexing (document details)
Advisor: Korosteleva, Olga
Commitee: Safer, Alan, Suaray, Kagba
School: California State University, Long Beach
Department: Mathematics and Statistics
School Location: United States -- California
Source: MAI 55/02M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Statistics
Keywords: Equation, Estimation, Modeling, Sem, Structural
Publication Number: 1602758
ISBN: 9781339186948
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