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

: The text covers the full range of SEM, including: Structural Equation Models: From Paths to Networks

: Discussed extensively, including its differences from PLS regression. (2019) by J

: 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. Core Themes and Historical Context : The text

: The book explains how SEM accommodates unobservable theory constructs (like "intelligence" or "satisfaction") through latent variables, which is a critical feature for social science research.

Westland places a strong emphasis on research design and data adequacy, addressing topics often neglected in standard "cookbook" textbooks.