Published titles in the Multivariate Applications Series series

Applied Data Analytic Techniques For Turning Points Research

Edited by Patricia Cohen

This innovative volume demonstrates the use of a range of statistical approaches that examine "turning points" (a change in direction, magnitude, or meaning) in real data. Analytic techniques are illustrated with real longitudinal data from a variety of fields. As such the book will appeal to a variety of researchers including:

Developmental researchers interested in identifying factors precipitating turning points at various life stages.
Medical or substance abuse researchers looking for turning points in disease or recovery.
Social researchers interested in estimating the effects of life experiences on subsequent behavioral changes.
Interpersonal behavior researchers looking to identify turning points in relationships.
Brain researchers needing to discriminate the onset of an experimentally produced process in a participant.

The book opens with the goals and theoretical considerations in defining turning points. An overview of the methods presented in subsequent chapters is then provided. Chapter goals include discriminating "local" from long-term effects, identifying variables altering the connection between trajectories at different life stages, locating non-normative turning points, coping with practical distributional problems in trajectory analyses, and changes in the meaning and connections between variables in the transition to adulthood. From an applied perspective, the book explores such topics as antisocial/aggressive trajectories at different life stages, the impact of imprisonment on criminal behavior, family contact trajectories in the transition to adulthood, sustained effects of substance abuse, alternative models of bereavement, and identifying brain changes associated with the onset of a new brain process.

Ideal for advanced students and researchers interested in identifying significant change in data in a variety of fields including psychology, medicine, education, political science, criminology, and sociology.

Published March 15th 2008 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Introduction to Statistical Mediation Analysis

By David MacKinnon

This volume introduces the statistical, methodological, and conceptual aspects of mediation analysis. Applications from health, social, and developmental psychology, sociology, communication, exercise science, and epidemiology are emphasized throughout. Single-mediator, multilevel, and longitudinal models are reviewed. The author's goal is to help the reader apply mediation analysis to their own data and understand its limitations.

Each chapter features an overview, numerous worked examples, a summary, and exercises (with answers to the odd numbered questions). The accompanying CD contains outputs described in the book from SAS, SPSS, LISREL, EQS, MPLUS, and CALIS, and a program to simulate the model. The notation used is consistent with existing literature on mediation in psychology.

The book opens with a review of the types of research questions the mediation model addresses. Part II describes the estimation of mediation effects including assumptions, statistical tests, and the construction of confidence limits. Advanced models including mediation in path analysis, longitudinal models, multilevel data, categorical variables, and mediation in the context of moderation are then described. The book closes with a discussion of the limits of mediation analysis, additional approaches to identifying mediating variables, and future directions.

Introduction to Statistical Mediation Analysis is intended for researchers and advanced students in health, social, clinical, and developmental psychology as well as communication, public health, nursing, epidemiology, and sociology. Some exposure to a graduate level research methods or statistics course is assumed. The overview of mediation analysis and the guidelines for conducting a mediation analysis will be appreciated by all readers.

Published January 17th 2008 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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A Paul Meehl Reader

Essays on the Practice of Scientific Psychology

Edited by Niels G. Waller, Leslie J. Yonce, William M. Grove, David Faust, Mark F. Lenzenweger

This new book introduces a new generation to the important insights of Paul Meehl. In addition to selected papers from the classic reader, Psychodiagnosis, this book features new material selected from Meehl's most influential writings. The resulting collection is a tour de force illustrating quantitative analysis of life science problems, an examination of the inadequacy of some methods of analysis, and a review of the application of taxometrics.

A Paul Meehl Reader is organized into five content areas: theory building and appraisal - how we discover and test the true causal relations of psychological constructs; specific etiology - an examination of genetic, behavioral, and environmental etiology in psychopathology; diagnosis and prediction - a review of the appropriate use of base rates; taxometrics - a look at Meehl's development of the method he invented; thinking effectively about psychological questions - a critique of correlation research and the power of quantitative thinking in psychology.

The Reader features section introductions to orient the reader and provide a context and structure for Paul Meehl's work. The section on diagnosis and prediction features problem sets with solutions to guide the reader through practical applications of the principles described. An accompanying DVD contains footage from Paul Meehl's engaging seminar on clinical versus statistical prediction. This book appeals to advanced students and professionals in psychology, sociology, law, education, human development, and philosophy.

Published April 7th 2006 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Structural Equation Modeling With EQS

Basic Concepts, Applications, and Programming

By Barbara Byrne

Readers who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text. Written specifically for those with little to no knowledge of structural equation modeling (SEM) or EQS, the author's goal is to provide a non-mathematical introduction to the basic concepts of SEM by applying these principles to EQS, Version 6.1. The book clearly demonstrates a wide variety of SEM/EQS applications that include confirmatory factor analytic and full latent variable models.

Written in a "user-friendly" style, the author "walks" the reader through the varied steps involved in the process of testing SEM models: model specification and estimation, assessment of model fit, EQS output, and interpretation of findings. Each of the book's applications is accompanied by: a statement of the hypothesis being tested, a schematic representation of the model, explanations of the EQS input and output files, tips on how to use the pull-down menus, and the data file upon which the application is based. The book carefully works through applications starting with relatively simple single group analyses, through to more advanced applications, such as a multi-group, latent growth curve, and multilevel modeling.

The new edition features:

many new applications that include a latent growth curve model, a multilevel model, a second-order model based on categorical data, a missing data multigroup model based on the EM algorithm, and the testing for latent mean differences related to a higher-order model;
a CD enclosed with the book that includes all application data;
vignettes illustrating procedural and/or data management tasks; and
description of how to build models both interactively using the BUILD-EQ interface and graphically using the EQS Diagrammer.

Published February 17th 2006 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Contemporary Psychometrics

Edited by Albert Maydeu-Olivares, John J. McArdle

Contemporary Psychometrics features cutting edge chapters organized in four sections: test theory, factor analysis, structural equation modeling, and multivariate analysis.

The section on test theory includes topics such as multidimensional item response theory (IRT), the relationship between IRT and factor analysis, estimation and testing of these models, and basic measurement issues that are often neglected.

The factor analysis section reviews the history and development of the model, factorial invariance and factor analysis indeterminacy, and Bayesian inference for factor scores and parameter estimates.

The section on structural equation modeling (SEM) includes the general algebraic-graphic rules for latent variable SEM, a survey of goodness of fit assessment, SEM resampling methods, a discussion of how to compare correlations between and within independent samples, dynamic factor models based on ARMA time series models, and multi-level factor analysis models for continuous and discrete data.

The final section on multivariate analysis includes topics such as dual scaling of ordinal data, model specification and missing data problems in time series models, and a discussion of the themes that run through all multivariate methods.

This tour de force through contemporary psychometrics will appeal to advanced students and researchers in the social and behavioral sciences and education, as well as methodologists from other disciplines.

Published April 8th 2005 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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The Essence of Multivariate Thinking

Basic Themes and Methods

By Lisa L. Harlow

The Essence of Multivariate Thinking is intended to make multivariate statistics more accessible to a wide audience. To encourage a more thorough understanding of multivariate methods, author Lisa Harlow suggests basic themes that run through most statistical methodology. The most pervasive theme is multiplicity. The author argues that the use of multivariate methods encourages multiple ways of investigating phenomena. She explains that widening our lens to identify multiple theories, constructs, measures, samples, methods, and time points provide greater reliability and validity in our research. Dr. Harlow then shows how these themes are applied to several multivariate methods, with the hope that this will ease understanding in the basic concepts of multivariate thinking. Formulas are kept at a minimum.

The first three chapters review the core themes that run through multivariate methods. Seven different multivariate methods are then described using 10 questions that illuminate the main features, uses, multiplicity, themes, interpretations, and applications. The seven methods covered are multiple regression, analysis of covariance, multivariate analysis of variance, discriminant function analysis, logistic regression, canonical correlation, and principal components/factor analysis. The final chapter pulls together the principal themes and features charts that list common themes and how they pertain to each of the methods discussed.

The Essence of Multivariate Thinking, features:

A unique focus on the underlying themes that run through most multivariate methods.
A dual focus on significance tests and effect sizes to encourage readers to adopt a thorough approach to assessing the significance and magnitude of their findings.
A detailed example for each method to delineate how the multivariate themes apply.
Tabular results from statistical analysis programs that mirror sections of the output files.
A common dataset throughout the chapters to provide continuity with the variables and research questions.
A CD with data, SAS program setup and output, homework exercises, and chapter lectures.

This book is useful to advanced students, professionals, and researchers interested in applying multivariate methods in such fields as behavioral medicine, social, health, personality, developmental, cognitive, and industrial-organizational psychology, as well as in education and evaluation. A preliminary knowledge of basic statistics, research methods, basic algebra, and finite mathematics is recommended.

Published January 18th 2005 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Multilevel Modeling

Methodological Advances, Issues, and Applications

Edited by Steven P. Reise, Naihua Duan

This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world.

The book's goal is to critically examine the real problems that occur when trying to use MLMs in applied research, such as power, experimental design, and model violations. This presentation of cutting-edge work and statistical innovations in multilevel modeling includes topics such as growth modeling, repeated measures analysis, nonlinear modeling, outlier detection, and meta analysis.

This volume will be beneficial for researchers with advanced statistical training and extensive experience in applying multilevel models, especially in the areas of education; clinical intervention; social, developmental and health psychology, and other behavioral sciences; or as a supplement for an introductory graduate-level course.

Published December 1st 2003 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Modeling Intraindividual Variability With Repeated Measures Data

Methods and Applications

Edited by D. S. Moskowitz, Scott L. Hershberger, D.S. Moskowitz

This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable.

It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques.

Each chapter features:

a minimum discussion of mathematical detail;
an empirical example applying the technique; and
a discussion of the software related to that technique.

Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.

Published October 1st 2001 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Conducting Meta-Analysis Using SAS

By Jr., Winfred Arthur, Winston Bennett, Allen I. Huffcutt

Conducting Meta-Analysis Using SAS reviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches.

This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material.

Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.

Published June 1st 2001 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Structural Equation Modeling With AMOS

Basic Concepts, Applications, and Programming

By Barbara Byrne

This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and applications of structural equation modeling; 2) demonstrating basic applications of SEM using AMOS 4.0; and 3) highlighting features of AMOS 4.0 that address important caveats related to SEM analyses.

Written in a "user-friendly" style, the author "walks" the reader through 10 SEM applications from model specification to estimation to the assessment and interpretation of the output. Each of the book's applications is accompanied by:

a statement of the hypothesis being tested;
a schematic representation of the model under study;
the use and function of a wide variety of icons and pull-down menus;
a full explanation of related AMOS Graphic input models and output files;
a model input file based on AMOS BASIC; and
the published reference from which each application was drawn.

Published April 1st 2001 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Item Response Theory for Psychologists

By Susan E. Embretson, Steven P. Reise

This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar psychological principles. It surveys contemporary IRT models, estimation methods, and computer programs. Polytomous IRT models are given central coverage since many psychological tests use rating scales.

Ideal for clinical, industrial, counseling, educational, and behavioral medicine professionals and students familiar with classical testing principles, exposure to material covered in first-year graduate statistics courses is helpful. All symbols and equations are thoroughly explained verbally and graphically.

Published May 1st 2000 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Multivariate Applications in Substance Use Research

New Methods for New Questions

Edited by Jennifer S. Rose, Laurie Chassin, Clark C. Presson, Steven J. Sherman

This edited volume introduces the latest advances in quantitative methods and illustrates ways to apply these methods to important questions in substance use research. The goal is to provide a forum for dialogue between methodologists developing innovative multivariate statistical methods and substance use researchers who have produced rich data sets.

Reflecting current research trends, the book examines the use of longitudinal techniques to measure processes of change over time. Researchers faced with the task of studying the causes, course, treatment, and prevention of substance use and abuse will find this volume helpful for applying these techniques to make optimal use of their data.

This innovative volume:

introduces the use of latent curve methods for describing individual trajectories of adolescent substance use over time;
explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups;
demonstrates how different patterns of missing data influence the interpretation of results;
reports on some recent advances in longitudinal growth modeling;
illustrates methods to assess mediation when there are multiple mediating pathways underlying an intervention effect;
describes methods to identify moderating relations in structural equation models;
demonstrates the use of structural equation models to evaluate a preventive intervention;
applies epidemic modeling techniques to understand the spread of substance use in society;
illustrates the use of latent transition analysis to model substance use as a series of stages; and
applies logistic regression to prospectively predict smoking cessation.

Published January 1st 2000 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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Structural Equation Modeling With Lisrel, Prelis, and Simplis

Basic Concepts, Applications, and Programming

By Barbara Byrne

This book illustrates the ease with which various features of LISREL 8 and PRELIS 2 can be implemented in addressing research questions that lend themselves to SEM. Its purpose is threefold: (a) to present a nonmathmatical introduction to basic concepts associated with SEM, (b) to demonstrate basic applications of SEM using both the DOS and Windows versions of LISREL 8, as well as both the LISREL and SIMPLIS lexicons, and (c) to highlight particular features of the LISREL 8 and PRELIS 2 progams that address important caveats related to SEM analyses.

This book is intended neither as a text on the topic of SEM, nor as a comprehensive review of the many statistical funcitons available in the LISREL 8 and PRELIS 2 programs. Rather, the intent is to provide a practical guide to SEM using the LISREL approach. As such, the reader is "walked through" a diversity of SEM applications that include both factor analytic and full latent variable models, as well as a variety of data management procedures.

Published March 1st 1998 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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What If There Were No Significance Tests?

Edited by Lisa L. Harlow, Stanley A. Mulaik, James H. Steiger

This book is the result of a spirited debate stimulated by a recent meeting of the Society of Multivariate Experimental Psychology. Although the viewpoints span a range of perspectives, the overriding theme that emerges states that significance testing may still be useful if supplemented with some or all of the following -- Bayesian logic, caution, confidence intervals, effect sizes and power, other goodness of approximation measures, replication and meta-analysis, sound reasoning, and theory appraisal and corroboration.

The book is organized into five general areas. The first presents an overview of significance testing issues that sythesizes the highlights of the remainder of the book. The next discusses the debate in which significance testing should be rejected or retained. The third outlines various methods that may supplement current significance testing procedures. The fourth discusses Bayesian approaches and methods and the use of confidence intervals versus significance tests. The last presents the philosophy of science perspectives.

Rather than providing definitive prescriptions, the chapters are largely suggestive of general issues, concerns, and application guidelines. The editors allow readers to choose the best way to conduct hypothesis testing in their respective fields. For anyone doing research in the social sciences, this book is bound to become "must" reading.

Published August 1st 1997 by Psychology Press (formerly published by Lawrence Erlbaum Associates).

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