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 ...

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 ...

Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...

Structural Equation Modeling (SEM) is a statistical technique that allows researchers to examine complex relationships between observed and latent variables. In the context of, for example, ...

Malnutrition, i.e., under-nutrition and over-nutrition, in terms of overweight and obese keep rising in all segments of the population, but disproportionately affecting children and adolescents. The ...

Latent factors are variables that cannot be observed directly but can be inferred from a set of observable variables. For example, in psychology, bad conduct (latent factor) can be measured by how ...