(2019) by J. Christopher Westland is a concise reference that explores the evolution and application of Structural Equation Modeling (SEM). It is unique for showcasing a wide range of methodologies—from historical path analysis to modern neural network-based approaches—rather than focusing on just one school of thought. Core Themes and Historical Context
: It traces SEM back to the natural sciences, specifically biology and Sewall Wright’s (1921) path analysis , which was developed to make sense of diverse biological observations. Structural Equation Models: From Paths to Networks
Westland places a strong emphasis on research design and data adequacy, addressing topics often neglected in standard "cookbook" textbooks. (2019) by J
: Contemporary methods that expand SEM's ability to map complex, naturally occurring networks. Key Technical Insights Core Themes and Historical Context : It traces
The book frames SEM methodologies within their proper historical context to help researchers understand the specific strengths and weaknesses of different methods.