: Focuses on the "why" and "how" of SEM rather than just the underlying matrix algebra.
: While it uses examples from tools like Amos, Mplus , and lavaan (R) , the principles remain applicable across platforms.
: Provides a step-by-step roadmap for specification, identification, estimation, and testing.
: Encourages researchers to avoid "canned" interpretations and instead engage deeply with their theoretical models. Key Content Areas
