Understanding Structural Equation Models
Models of Relationships Between Variables

About the book: This text is designed for those who wish to move beyond plug-and-play SEM to a deeper, more philosophical and data-conscious understanding. The worked examples, and emphasis on skepticism will help build confidence in using SEM flexibly and responsibly for a broad range of social and behavioral science research.

Key Features

• • Emphasis on multiverse analysis, right-sizing statistical models to data, and the generation of plausible skeptical alternatives

  • Robust assumption checking (loess regression, regression and SEM diagnostics).

  • Detailed, visual coverage of a variety of path diagrams, their links to matrix-based specifications and data exploration using heat-map visualization and tests of dimensionality.

  • A variety of SEMs including mediational models, psychometrics (e.g., parallel, tau-equivalent, congeneric measurement), growth curve models, exploratory factor analysis, multi-group, categorical, and exploratory structural equation modelling (ESEM).

Chapter Resources