Bücher der Reihe Multivariate Applications Series

This book is intended as a celebration of the seminal work of Rod McDonald's career and covers a wide range of topics in psychometrics.

The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.

The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.

With the aid of this book's user friendly style, readers gain a greater understanding of sophisticated multivariate techniques and how to apply them to substance use research questions.

This handbook reviews classic and emerging IRT methods and applications that are revolutionizing psychological measurement, particularly for health outcome assessments used to demonstrate treatment effectiveness. Conceptual and statistical issues confronting researchers in psychology, education, and medicine are addressed including multidimensional and explanatory models. World renowned contributors offer examples using real data, some from NIH-PROMIS. The book reviews the most significant IRT models and the obstacles that arise in their application. Each chapter reviews the current literature and describes related research methods, applies the material, and suggests future directions.

This handbook reviews classic and emerging IRT methods and applications that are revolutionizing psychological measurement, particularly for health outcome assessments used to demonstrate treatment effectiveness. Conceptual and statistical issues confronting researchers in psychology, education, and medicine are addressed including multidimensional and explanatory models. World renowned contributors offer examples using real data, some from NIH-PROMIS. The book reviews the most significant IRT models and the obstacles that arise in their application. Each chapter reviews the current literature and describes related research methods, applies the material, and suggests future directions.

This volume provides statisticians and graduate students with a comprehensive view of structural equation modeling using several different command languages.

Modeled after Barbara Byrne's other best-selling structural equation modeling (SEM) books, this practical guide reviews the basic concepts and applications of SEM using Mplus Versions 5 & 6. The author reviews SEM applications based on actual data taken from her own research. Using non-mathematical language, it is written for the novice SEM user. With each application chapter, the author "walks" the reader through all steps involved in testing the SEM model including: an explanation of the issues addressed illustrated and annotated testing of the hypothesized and post hoc models explanation and interpretation of all Mplus input and output files important caveats pertinent to the SEM application under study a description of the data and reference upon which the model was based the corresponding data and syntax files available under "Supplementary Material" below The first two chapters introduce the fundamental concepts of SEM and important basics of the Mplus program. The remaining chapters focus on SEM applications and include a variety of SEM models presented within the context of three sections: Single-group analyses, Multiple-group analyses, and other important topics, the latter of which includes the multitrait-multimethod, latent growth curve, and multilevel models. Intended for researchers, practitioners, and students who use SEM and Mplus, this book is an ideal resource for graduate level courses on SEM taught in psychology, education, business, and other social and health sciences and/or as a supplement for courses on applied statistics, multivariate statistics, intermediate or advanced statistics, and/or research design. Appropriate for those with limited exposure to SEM or Mplus, a prerequisite of basic statistics through regression analysis is recommended.

First Published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

This work covers topics such as meta-analysis of effect sizes, meta-analysis of correlations and conversion and transformation equations.

Beginning with an overview of the basic concepts of SEM and the EQS program, this book works through applications starting with simple single group analyses, through to more advanced applications, such as a multi-group, latent growth curve, and multilevel modeling. It provides a non-mathematical introduction to the basic concepts of SEM.

First Published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

This volume provides innovative, practical and clear guidance for students who are training to teach statistics and quantitative methods to undergraduates or who are already teaching and want to improve their knowledge and skills. It also inspires instructors to think critically about their teaching of statistics and quantitative methods.

This volume presents a collection of chapters on the study of multivariate change, focusing on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes.