Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl's structural causal model), and composite SEM (partial least squares path modeling). With increased emphasis on freely available software tools such as the R lavaan package, the text uses data examples from multiple disciplines to provide a comprehensive understanding of all phases of SEM--what to know, best practices, and pitfalls to avoid. It includes exercises with answers, rules to remember, topic boxes, and a new self-test on significance testing, regression, and psychometrics. The companion website supplies helpful primers on these topics as well as data, syntax, and output for the book's examples, in files that can be opened with any basic text editor. New to This Edition *Chapters on composite SEM, also called partial least squares path modeling or variance-based SEM; conducting SEM analyses in small samples; and recent developments in mediation analysis. *Coverage of new reporting standards for SEM analyses; piecewise SEM, also called confirmatory path analysis; comparing alternative models fitted to the same data; and issues in multiple-group SEM. *Extended tutorials on techniques for dealing with missing data in SEM and instrumental variable methods to deal with confounding of target causal effects. Pedagogical Features *New self-test of knowledge about background topics (significance testing, regression, and psychometrics) with scoring key and online primers. *End-of-chapter suggestions for further reading and exercises with answers. *Troublesome examples from real data, with guidance for handling typical problems in analyses. *Topic boxes on special issues and boxed rules to remember. *Website promoting a learn-by-doing approach, including data, extensively annotated syntax, and output files for all the book's detailed examples.

Originally published in 1979, this title represents a summary of 17 years of research centring around the "Sensation Seeking Scale" (SSS) and the theory from which the test was derived. Now an integral part of personality testing, including adaptations for use with children, this reissue is a chance to see where it all began.

First Published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.

Originally published in 1987, this book presents papers from the First Conference of European Clinical Psychologists, held at the University of Kent Canterbury in July of that year. It shows some of the most exciting and recent developments in research and innovations in professional practice from many European countries with an overall theme of the WHO strategy of Health for all by the year 2000. The whole range of clinical psychology is covered, including: cognitive therapy, clinical psychology and WHO strategy, the mental health of ethnic minority groups, health psychology, care in the community, and many other topics. The book is likely to be of interest for anyone concerned with the recent history and policies in clinical psychology."

The Children's Court is one of society's most important social institutions. At the same time, it is steeped in controversy. This is in large measure due to the persistence and complexity of the problems with which it deals, namely, juvenile crime and child abuse and neglect. Despite the importance of the Children's Court as a means of holding young people accountable for their anti-social behaviour and parents for the care of their children, it has not been the subject of close study. Certainly it has not been previously studied nationally. This book, an edited collection, is based on the findings of study that spanned the six States and two Territories of Australia. The study sought to examine the current challenges faced by the Children's Court and to identify desirable and feasible directions for reform in each State and Territory. A further unique feature of this study is that it canvassed the views of judges and magistrates who preside over this court.

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book's examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter's exercises. Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.

Devising tests that evaluate a nation's educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design. The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST. Intended for psychologists, social scientists, and educational measurement scientists, this volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions. Winner of the 2016 AERA Award for Significant Contribution to Educational Measurement and Research Methodology The 2016 American Education Research Association (AERA) Div. D award committee for Significant Contributions to Educational Measurement and Research Methodology has recognized unanimously this collaborative work advancing the theory and applications of computerized MST. This annual award recognizes published research judged to represent a significant conceptual advancement in the theory and practice of educational measurement and/or educational research methodology. The 2016 award was made under the heading: Measurement, Psychometrics, and Assessment. This collective work, published in 2014 as an edited volume titled Computerized Multistage Testing: Theory and Applications, was cited by the committee both for the originality of the conceptual foundations presented in support of multistage testing and for arguing persuasively for its potential impact on the practice of educational measurement.

*Invaluable school practitioner resource, revised and updated: 25% new material includes telehealth applications, cyberbullying updates, and more. *Expanded coverage of adolescent issues, such as antisocial behavior, substance use, social media, sexual orientation, and gender identity. *Practice-oriented work gives psychologists, counselors, social workers, and educators ready-to-use, downloadable tools. *Authoritative, research-based information.

The encouraging book that has guided thousands of students step by step through crafting a strong dissertation proposal is now in a thoroughly revised second edition. It includes new guidance for developing methodology-specific problem statements, an expanded discussion of the literature review, coverage of the four-chapter dissertation model, and more. Terrell demonstrates how to write each chapter of the proposal, including the problem statement, purpose statement, and research questions and hypotheses; literature review; and detailed plans for data collection and analysis. "Let's Start Writing" exercises serve as building blocks for drafting a complete proposal. Other user-friendly features include case-study examples from diverse disciplines, "Do You Understand?" checklists, and end-of-chapter practice tests with answers. Appendices present an exemplary proposal written three ways to demonstrate quantitative, qualitative, and mixed methods approaches, and discuss how to structure a four-chapter dissertation. New to This Edition *Introduction offering a concise overview of the entire proposal-writing process and the doctoral experience. *Additional help with tailoring problem and purpose statements for quantitative, qualitative, and mixed-methods studies. *Expanded discussion of the review of literature, including a criterion for judging the quality of primary versus secondary sources. *Many new examples from different disciplines, such as studies of depression treatments, approaches to reducing offender recidivism, health effects of irradiated crops, strength training in college football, and remote teaching and learning during COVID-19. *Focus on the five-chapter model is broadened to include specific guidance for four-chapter dissertations. *Broader, more detailed reference list and glossary.

This is a book about communication behavior: how we conceptualize it, observe it, measure it, and analyze it. The 1970s and 1980s were times when communication behavior was a primary interest of many communication scholars. The aim of this book is to reignite some interest in and passion about how human communication behavior should be studied. It presents the best advice, techniques, cautions, and controversies from the 1970s and 1980s and then updates them. Several chapters also introduce statistical methods and procedures to allow readers to analyze behavioral data. This book is a useful resource for communication scholars and graduate students to guide their study of communication behavior.

The book covers the topic of experimental instrumentation at the turn of the 20th century. The authors introduce the role of instruments in the process of establishing psychology as a science. They concentrate on identifying historical devices and problems with rediscovering their functionality. The core of the book consists of a categorized list of instruments with a description of their purpose and mechanical design. The categorization covers recording and time measuring devices, instruments designated for the research of human senses, memory and learning, and devices for physiological measurement. The publication also includes a companion website with short videos demonstrating selected instruments in action.

This new monograph presents Dr. Luce's current understanding of the behavioral properties people exhibit (or should exhibit) when they make selections among alternatives and how these properties lead to numerical representations of those preferences. It summarizes, and places in historical perspective, the research Dr. Luce has done on utility theory for over 10 years. Included are axiomatic theoretical formulations, experiments designed to test individual assumptions, and analyses of the fit to bodies of data of numerical representations derived from the theory.

In a managed care era, the MMPI-2 is becoming an overloaded workhorse, required to generate more and more of the assessments that a battery of instruments once did. Though all now rely on the MMPI-2 for good reasons, and the MMPI has fallen out of use entirely, some important and clinically useful scales were lost in the transition. Edward Gotts and Thomas Knudsen have recovered these scales and integrated them with all the standard MMPI-2 scales, the recently published Restructured Clinical Scales, and a number of scales they have constructed to assess positive strengths and coping abilities, and response consistency-inconsistency. This book lays out their new Content Cluster interpretive approach. Drawing on data from a large psychiatric inpatient sample, they present item composition, reliability, and validity information for each recovered and new scale, and convincingly demonstrate that their new Content Cluster approach results in improved prediction and interpretive power. They also show how to conjoin Rorschach and MMPI-2 results in more effective assessment strategies, and how to tie MMPI-2 results to specific DSM-IV criteria. The Clinical Interpretation of the MMPI-2: A Content Cluster Approach offers psychologists essential new tools for clinical and personality assessment.

This book focuses on how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.

The first edition of Personality Assessment provided an overview of the most popular self-report and performance-based personality assessment instruments. The chapter authors were key members in creating or developing the research base for the eight test instruments covered in the book. The text was geared with graduate-level clinical, school, and counseling psychology courses in mind. While still retaining all the attractive features of the first edition, this revision will reflect the advances in the field since 2008. Chapter contributors updated and expanded on reliability and validity data, clinical utility, multicultural considerations, and implications for therapeutic assessment. Another distinctive feature of this second edition is a companion website that features ancillary materials such as PowerPoints and test banks.

The goal of the chapters in this SIOP Organizational Frontiers Series volume is to challenge researchers to break away from the rote application of traditional methodologies and to capitalize upon the wealth of data collection and analytic strategies available to them. In that spirit, many of the chapters in this book deal with methodologies that encourage organizational scientists to re-conceptualize phenomena of interest (e.g., experience sampling, catastrophe modeling), employ novel data collection strategies (e.g., data mining, Petri nets), and/or apply sophisticated analytic techniques (e.g., latent class analysis). The editors believe that these chapters provide compelling solutions for the complex problems faced by organizational researchers.

This book is an interdisciplinary guide to empirical research on nonverbal behaviour. It focuses on tools and procedures to investigate body movement and gesture and the relation to cognitive, emotional, and interactive processes. NEUROGES is an objective and reliable coding system for movement behaviour and gesture. Its combination with the multi-media annotation tool ELAN results in an effective movement analysis. Rater training and rating procedures constitute an important component in movement behaviour studies. A novel algorithm assesses interrater agreement for the segmentation of the ongoing flow of behaviour. Recommendations for study designs and statistical data evaluation are given, including innovative procedures for the analysis of interactive partners' body movements.

This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond "frequentist" concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called "hypothesis testing") problems most frequently encountered in real-world applications.

Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data. It also provides a way to quantify and analyze individual differences, such as developmental and neuropsychological, in the context of a model of the overall group effects. To harness the practical aspects of this useful tool, behavioral science researchers need a concise, accessible resource that explains how to implement these analysis methods. Growth Curve Analysis and Visualization Using R provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. The book begins with discussing problems encountered when analyzing time course data, how to visualize time course data using the ggplot2 package, and how to format data for GCA and plotting. It then presents a conceptual overview of GCA and the core analysis syntax using the lme4 package and demonstrates how to plot model fits. The book describes how to deal with change over time that is not linear, how to structure random effects, how GCA and regression use categorical predictors, and how to conduct multiple simultaneous comparisons among different levels of a factor. It also compares the advantages and disadvantages of approaches to implementing logistic and quasi-logistic GCA and discusses how to use GCA to analyze individual differences as both fixed and random effects. The final chapter presents the code for all of the key examples along with samples demonstrating how to report GCA results. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. Each chapter ends with exercises to test your understanding. The example datasets, code for solutions to the exercises, and supplemental code and examples are available on the author's website.

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.

Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

YIS has been thought as an annual series of volumes collecting contributes aimed at developing the integration of idiographic and nomothetic approaches in psychological and more in general social science. At the beginning, 3 years ago, we got an agreement with an Italian publisher (FGP - Firera Publishing Group) interested in the scientific project and therefore willing to help the start up of this scientific enterprise. After publishing the first volume (YIS 2008- yet published in 2009 - the Volume is freely available on the FPG's website) we have had many positive feedbacks and signals of interests, as well as several submissions, from many parts of the world . This has provided an acceleration of the following issues - Above all, this led us to realize that it was time to give an editorial collocation to YIS that can be more consistent with the interest it has raised and that can ulteriorly raise. FPG does not put constraint on this perspective, being aware and agreed of the necessity of a worldwide context for the YIS's development. Moreover, there are no constraints in the possibility of going on in using the label "YIS," starting from Volume 4 The Series addresses a quite large potential public - students and researchers interested to theoretical and methodological development of psychology and, more in general, social science. Persons engaged with qualitative, dynamic informed models of analysis will find YIS a precious tool as well as a context enabling to develop a worlwide network of practices and cultures of research. The first three volumes' TOC witness how large and constantly increasing is the interest around the scientific project.

Assessing Adolescents with the MACI is an interpretive guide for using the Millon Adolescent Clinical Inventory—the most widely used personality assessment test for adolescents. The first book devoted exclusively to the MACI, this resource will prove a helpful guide for understanding the test, interpreting the results in clinical evaluation, and making appropriate recommendations for treatment and care management.

Unlike other assessment tests developed for adults and adapted for adolescents, the MACI was created to address the unique concerns, pressures, and situations of adolescents. The MACI is also constructed using an underlying theory of personality and psychopathology. The MACI is a 160-item, 31-scale self report inventory that was designed to assess personality styles, significant problems or concerns, and clinical symptoms in adolescents. Using a true false format, the MACI surveys a wide range of personality characteristics and clinical symptoms that tend to be a focus in psychological evaluations of teenagers that either have or are suspected of having emotional or behavioral difficulties.

While multi-scale personality inventories such as the MACI are useful for improving the clinician's understanding of an adolescent's personality and clinical symptoms, there are other reasons for using such instruments. The MACI can be used to formulate diagnostic hypotheses, confirm clinical diagnoses, formulate treatment plans, or assist in decision making surrounding case management and disposition planning. The MACI can be used as an outcome measure to evaluate changes in an adolescent's functioning as a result of treatment and intervention. Of course, the MACI can also be used in research studies to investigate a range of issues that pertain to adolescent psychopathology, personality, and treatment response.

Drawing on a broad range of sources, including data in the MACI manual, published research studies, unpublished research, theoretical literature, and his own experience with the test, Joseph McCann lays the groundwork for the basis of the test and then offers an exhaustive exploration of all facets of the test. Recognizing both the strengths and weaknesses of the MACI, McCann offers a balanced and comprehensive resource on this vital assessment tool.

"This book fills an important gap in the clinical literature . . . Joseph McCann, author of this first full text on the MACI, is the best known workshop presenter on the topic. Assessment with the MACI will enable the student and the clinician to develop a sophisticated basis for disentangling the many variations among youngsters, to assess both their assets and liabilities, to determine the presence of clinical disorders, and, most importantly, to provide a full picture that can serve as the basis for making decisions regarding each adolescent's welfare, that is, to be able to outline a logical course of treatment which may prove more optimally efficacious. It will guide the reader to transform the raw MACI test data, coordinate these data with the history of the youngster's experience, as well as with observational and interview information, facilitating interpretive syntheses and providing thereby a basis to help link assessment to psychotherapy. This text is insightful and comprehensive, a work of inestimable value to both practicing clinicians and students." —Theodore Millon, from the Foreword.

This is the first book to demonstrate the application of power analysis to the newer more advanced statistical techniques that are increasingly used in the social and behavioral sciences. Both basic and advanced designs are covered. Readers are shown how to apply power analysis to techniques such as hierarchical linear modeling, meta-analysis, and structural equation modeling. Each chapter opens with a review of the statistical procedure and then proceeds to derive the power functions. This is followed by examples that demonstrate how to produce power tables and charts. The book clearly shows how to calculate power by providing open code for every design and procedure in R, SAS, and SPSS. Readers can verify the power computation using the computer programs on the book's website. There is a growing requirement to include power analysis to justify sample sizes in grant proposals. Most chapters are self-standing and can be read in any order without much disruption.This book will help readers do just that. Sample computer code in R, SPSS, and SAS at www.routledge.com/9781848729810 are written to tabulate power values and produce power curves that can be included in a grant proposal. Organized according to various techniques, chapters 1 - 3 introduce the basics of statistical power and sample size issues including the historical origin, hypothesis testing, and the use of statistical power in t tests and confidence intervals. Chapters 4 - 6 cover common statistical procedures -- analysis of variance, linear regression (both simple regression and multiple regression), correlation, analysis of covariance, and multivariate analysis. Chapters 7 - 11 review the new statistical procedures -- multi-level models, meta-analysis, structural equation models, and longitudinal studies. The appendixes contain a tutorial about R and show the statistical theory of power analysis. Intended as a supplement for graduate courses on quantitative methods, multivariate statistics, hierarchical linear modeling (HLM) and/or multilevel modeling and SEM taught in psychology, education, human development, nursing, and social and life sciences, this is the first text on statistical power for advanced procedures. Researchers and practitioners in these fields also appreciate the book's unique coverage of the use of statistical power analysis to determine sample size in planning a study. A prerequisite of basic through multivariate statistics is assumed.

This book addresses issues related with researching sensitive topics in social work, focusing on marginalized, vulnerable and hard to reach people. It covers the definition, characteristics, challenges and opportunities of sensitive research, its philosophical roots and methodological debates, and the skills and values that are required along with the ethical, political and legal issues involved in conducting social work research. This book will cover innovative research methods appropriate for research on sensitive topics involving vulnerable people. It shines light on how to use traditional research methods sensitively, and how to generate data while minimizing the harm that can potentially be caused to research participants and researchers.