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Book Review: Motivational interviewing: Helping people change

ments. The companion website also offers application and interpretation of ANOVA and path analysis, as well as worked examples of univariate and bivariate analysis. Chapter 6 introduces ANOVA/ANCOVA. Topics covered here include calculations associated with ANOVA/ANCOVA (mean square within, mean square between, etc.), assumptions associated with ANOVA/ANCOVA, and two separate sections on interpreting model results, one examining ANOVA and the other ANCOVA. This chapter offers prescriptive instructions about how to conduct a one-way ANOVA, steps for conducting planned comparisons, and the steps for conducting post hoc comparisons. One of the great strengths of this Chapter concerns the presentation of contrast coding in locating significant bivariate relationships within ANOVA/ANCOVA. Here, the authors present a wellformulated discussion on how to use planned comparisons, as well as post hoc testing, with brief emphasis on the differences between each type of test (orthogonal vs. nonorthogonal planned contrasts, Scheffe vs. Tukey’s HSD vs. Fisher’s LSD post hoc testing, etc.). The final chapter (chapter 7) presents information on path analysis to readers. It presents well-crafted illustrative descriptions of path diagrams, key terms associated with path analysis (endogenous vs. exogenous variables, etc.), a discussion of direct versus indirect model effects, statistical assumptions, and an introduction to conducting path analysis using Analysis of Moment Structures software. In my opinion, the most valuable subsection of the entire text is a poignant discussion on how path analysis is similar, but not identical, to the analytical tool Structural Equation Modeling (SEM). There is one very important difference between SEM and path analysis, measurement models. SEM was developed to examine two dimensions of statistical testing simultaneously; the order of relationships among measured variables (structural models) and psychometric properties of latent variables (measurement models). However, for some, SEM has been co-opted as a rather generic tool used exclusively for path analysis because of its relaxed assumptions concerning the accuracy of variable measurement and simplistic measures concerning overall model fit. While there is no violation in using SEM solely as a tool for path analysis, current doctoral students will benefit substantially from reinforcement that path analysis is only one component of SEM, as SEM can also examine latent variable measurement models. Stylistically, the text is easy to read and simple to process. There is little reliance on mathematical representation and much simplicity in graphical and table-based information. However, there are a few shortcomings worth mentioning. First, the examples presented within the book and accompanying website are exclusively drawn from the 1988 National Educational Longitudinal Education Study (NELS). While this is indeed a superb data set for statistical modeling, not all readers will find the examples relevant to their own practice/ research. Additionally, some, but not all chapters have an additional readings subsection at their conclusion. These important subsections could easily be added to every chapter in the book and could have contained more specified readings. Many additional readings subsections offer references to other, well-known, statistics textbooks. Furthermore, while a strength of the book is that the authors place almost no assumptions on the reader’s prior statistical knowledge, speaking as an early career social worker, some may struggle to find this material challenging. This can be easily remedied through additional supplemental materials, advanced topics on the book’s corresponding website, or recommended readings explicitly for more advanced, detail-specific topics. Finally, additional multimedia offerings at the conclusion of each chapter may aid substantially in student learning, especially concerning the presentation of introductory ideas such as central tendency, variability, and hypothesis testing. With these minor criticisms in mind, the book is clear and well written, overall. It is easy to read and appropriate for its targeted audience. Indeed, each chapter is thorough in its presentation, while not letting the reader get too bogged down in theoretical notions of statistical testing or overwhelming mathematical equations. Additionally, an engaging instructor, course-specific supplemental readings, and in-class multimedia presentations can easily remedy many, if not all the minor stylistic shortcomings mentioned. This text should be considered a valuable and concise tool in learning and conducting social work research.