Structural Equation Models: From Paths — To Networks

(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

The book frames SEM methodologies within their proper historical context to help researchers understand the specific strengths and weaknesses of different methods. Core Themes and Historical Context : It traces

: The text covers the full range of SEM, including:

: Westland is known for a critical stance on certain methods; for instance, he famously characterizes PLS path modeling as potentially problematic for researchers interested in "bogus theories with random data". Practical Resource Information Structural Equation Models: From Paths to Networks