Estimating structural equation models within a bayesian framework: a concrete example of a markov chain monte carlo method
Jaehwa Choi · Biometrics & Biostatistics International Journal · 2018
Structural equation modeling (SEM; Bollen, 1 ) is a key latentvariable modeling framework in the social and behavioral sciences.It is generally used for understanding how observable indicators relate to latent variables that are postulated to represent unobservable constructs and how these latent variables influence each other.SEM can accommodate a variety of research questions including those that lead to multi-group estimation, multi-level estimation, missing data estimation, and longitudinal estimation, both in isolation and in combination.