In this issue

What's New in Books

Latest titles in the fields of quantitative and qualitative methodology.

“Structural Equation Modeling with AMOS” (3 rd ed.)
By Barbara M. Byrne
Published in June 2016 by Routledge ($55.95 paperback; $165 hardback)

This text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Because it uses clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter “walks” readers through the steps involved (specification, estimation, evaluation and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down menus; and data upon which the model application was based, together with updated references pertinent to the SEM model tested.

“Bayesian Psychometric Modeling”
By Roy Levy & Robert J. Mislevy
Published in May 2016 by CRC Press ($89.95 hardback; $62.97 e-book)

This book presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov-chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code and Netica files used in the examples.

“Handbook of Item Response Theory: Volume Two”
Edited by Wim J. van der Linden
Published in February 2016 by CRC Press ($139.95 hardback; $97.97 e-book)

Drawing on the work of internationally acclaimed experts in the field, this book presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void.

This volume covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data and model identification issues. It also addresses recent developments in parameter estimation and model fit/comparison.

“Growth Modeling: Structural Equation and Multilevel Modeling Approaches”
By Kevin J. Grimm, Nilam Ram, & Ryne Estabrook
To be published in September 2016 by Guilford Press ($59.50 hardback; $59.50 e-book)

G rowth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates innovative ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, among other topics. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output and interpretation of each model's results.