Book review: Structural Equation Modelling for Social and Personality Psychology

I enjoy reading statistics and methods textbooks in my spare time. That’s probably not a trait I share with a lot of people, but I continue nonetheless. I also enjoy endless searches through Amazon, forum threads, and other review websites to make sure I’m picking the best book on any given subject. Together, those traits mean that over the past year or so I’ve read through a decent number of very good textbooks on useful research topics. I thought I’d start writing reviews of some of those texts in the (somewhat optimistic) hope that others might find them useful.

I recently finished ‘Structural Equation Modelling for Personality and Social Psychology’, part of a series of books aimed at giving an accessible introduction to a research method, pitched directly at personality and social psychologists. The author, Rick Hoyle, states in the foreword that this book’s purpose is to take researchers with a knowledge of analysis of variance and regression, and instill in them the basics of structural equation modelling (SEM). I found the book to be an excellent introduction to the topic, and felt that the description of a ‘nontechnical overview’ is a bit of an undersell. The book is certainly easy reading and not overly bogged down in formulae, but for all of that Hoyle manages to convey a fairly deep understanding of the mathematical underpinnings of SEM.

I feel that this book is ideal for researchers who, like myself, may have been using SEM for some time without a strong understanding of its underpinnings. Modern programs with friendly point-and-click interfaces let us specify and report structural equation models without truly understanding, for instance, that the measures of fit the program spits out are based on how well the implied covariance matrix reproduces the actual covariance matrix, or the requirements for full model identification (and even what identification means!). Reading this book has deepened my knowledge of the topic, and I feel much more confident in using SEM as a result. I would strongly recommend this book to anyone interested in gaining a firm grasp of structural equation modelling without delving into a formula-heavy textbook. I also feel that the “for Personality and Social Psychology” series as a whole is well-aimed. I found John Nezlek’s text on Multilevel modelling in the same series to be equally high quality, and will probably review that text in the future.