This comprehensive Handbook is the first to provide a practical, interdisciplinary review of ethical issues as they relate to quantitative methodology including how to present evidence for reliability and validity, what comprises an adequate tested population, and what constitutes scientific knowledge for eliminating biases. The book uses an ethical framework that emphasizes the human cost of quantitative decision making to help researchers understand the specific implications of their choices. The order of the Handbook chapters parallels the chronology of the research process: determining the research design and data collection; data analysis; and communicating findings. Each chapter: Explores the ethics of a particular topic Identifies prevailing methodological issues Reviews strategies and approaches for handling such issues and their ethical implications Provides one or more case examples Outlines plausible approaches to the issue including best-practice solutions. Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers' approach to data analysis are examined in Part 4 - when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process. This Handbook appeals to researchers and practitioners in psychology, human development, family studies, health, education, sociology, social work, political science, and business/marketing. This book is also a valuable supplement for quantitative methods courses required of all graduate students in these fields.

The second edition of this textbook provides expanded and updated guidance on the process of psychoeducational assessment and report writing for children in grades K-12. It casts the entire process within a newly proposed evidence-based psychoeducational assessment and report writing framework, and explains how to convey results through detailed, well-written reports. The new edition guides readers, step by step, through the assessment process - collecting data, writing reports, and communicating conclusions - for students with conditions spanning the range of IDEA classifications. Chapters offer a broad understanding of assessment and communication skills as well as the ethical, legal, cultural, and professional considerations that come with psychoeducational evaluation. In addition, chapters significantly expand on the coverage of learning disabilities, autism spectrum, intellectual disabilities, gifted, and other health-impaired and emotional disturbance assessment. The text updates sample reports from the previous edition, offering annotated commentary in the report explaining salient points and major decisions, and incorporates additional report samples to demonstrate fully the assessment and report writing process. Key topics addressed in the revised and expanded edition include: Psychoeducational assessment and report writing in school and clinic settings. Interview formats from various perspectives, including caregivers/parents, teachers, and students. Assessment of culturally and linguistically diverse youth. Assessment of social, emotional, behavioral and mental health difficulties that may affect students' educational functioning. Common academic difficulties, including reading, writing and mathematics. Common recommendations and accommodations for behavioral, social, emotional, and learning needs. Incorporation of response-to-intervention/curriculum based assessment data into the psychoeducational report. Psychoeducational Assessment and Report Writing, 2nd Edition, is an essential textbook for graduate students as well as researchers, professors, and professionals in child and school psychology, educational assessment, testing, and evaluation, social work, and related disciplines.

This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book's website http: //www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book's concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.

Cases and Stories of Transformative Action Research builds on its companion book, Principles and Methods of Transformative Action Research, by describing and analyzing dozens of examples of successful action research efforts pursued in the past five decades by students and faculty of the Western Institute for Social Research. Some projects are large-scale, and some are modest interventions in the everyday lives of those participating. Some are formal organizational efforts; others are the results of individual or small group initiatives. Included are chapters on community needs assessments and innovative grassroots approaches to program evaluation; the challenges of improving our decision-making during the crisis of the COVID-19 pandemic; strategies of intellectual activism in addressing the growing problem of workplace bullying; action research to preserve and share the history of the Omaha tribe; and plans for an innovative school-based project based on collaborative action-and-inquiry between students and Artificial Intelligence. In addition, there are a number of detailed stories about the use of transformative action research in such areas as somatic and trauma counseling, ethnic studies, health disparities, gender differences, grassroots popular education, and the improvement of statewide steps for preventing child abuse, among many others. This book can serve as an undergraduate or graduate social sciences text on research methods. It is also a guidebook for action-oriented research by academics, professionals, and lay people alike.

This book offers readers a uniquely detailed engagement with the ideas of legendary French psychoanalyst Jacques Lacan. The Freudian Thing is one of Lacan's most important texts, wherein he explains the significance and stakes of his "return to Freud" as a passionate defence of Freud's disturbing, epoch-making discovery of the unconscious, against misrepresentations and criticisms of it. However, Lacan is characteristically cryptic in The Freudian Thing. The combination of his writing style and vast range of references renders much of his thinking inaccessible to all but a narrow circle of scholarly specialists. Johnston's Irrepressible Truth opens up the universe of Lacanian psychoanalysis to much wider audiences by furnishing a sentence-by-sentence interpretive unpacking of this pivotal 1955 essay. In so doing, Johnston reveals the precision, rigor, and soundness of Lacan's teachings.

How do we measure happiness? Focusing on subjective measures as a proxy for welfare and well-being, this book finds ways to do that. Subjective measures have been used by psychologists, sociologists, political scientists, and, more recently, economists to answer a variety of scientifically and politically relevant questions. Van Praag, a pioneer in this field since 1971, and Ferrer-i-Carbonell present in this book a generally applicable methodology for the analysis of subjective satisfaction. Drawing on a range of surveys on people's satisfaction with their jobs, income, housing, marriages, and government policy, among other areas of life, this book shows how satisfaction with life "as a whole" is an aggregate of these domain satisfactions. Using German, British, Dutch, and Russian data, the authors cover a wide range of topics, even some not usually considered part of economic study. The book makes a distinction between actual satisfaction levels and individual norms, and in this way complements Van Praag's earlier work within the Leyden School with his later work in "happiness research". Among the many topics covered, the authors discuss: individuals' memory and anticipation processes and the estimation of adaptation phenomena (how individuals adapt to changing circumstances); the effect of reference groups on income norms and satisfaction with income; the importance of climate for well-being, including the development of a climate-equivalence index; the trade-offs between chronic diseases and income when well-being is kept constant; the damage of aircraft noise on well-being; the construction of a new talent tax tariff; and inequality from a satisfaction perspective, including the definition of "satisfaction inequalities", a natural extension of income inequality and poverty. This groundbreaking book presents new and fruitful methodology that consitutes a welcome addition to the social sciences.

This book is designed to give students and researchers the confidence to understand, assess, treat, and research test anxiety. Marty Sapp presents the various cognitive and behavioral theories of test anxiety along with instruments for measuring test anxiety. He integrates statistical methodology, measurement, and research designs with actual research situations that occur within the test anxiety field. In addition, the SPSS codes for conducting sample reliability and validity are provided along with the codes for finding confidence intervals around population reliability measures. Like the previous edition, the logic of structural equations modeling is presented with the EQS structural equations program. Many researchers view test anxiety as existing of factors such as Sarasons s four-factor model or Spielberger s two-factor model. Both models can be easily analyzed by EQS. In terms of treatment, affective, cognitive, behavioral, hypnosis, systematic desensitization, Eye-Movement Desensitization and Reprocessing (EMDR), and the Eye-Movement Technique (EMT) are presented. This book integrates applied research designs and statistical and measurement methodology that frequently occur in the test anxiety literature, but the methodological treatment of research is nonmathematical. Finally, extensive discussions of treatments for test anxiety are provided.

This comprehensive Handbook focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models originated, conceptually and in practical terms. Diverse perspectives on how these models can best be evaluated are also provided. Practical applications provide a realistic account of the issues practitioners face using these models. Disparate elements of the book are linked through editorial sidebars that connect common ideas across chapters, compare and reconcile differences in terminology, and explain variations in mathematical notation. These sidebars help to demonstrate the commonalities that exist across the field. By assembling this critical information, the editors hope to inspire others to use polytomous IRT models in their own research so they too can achieve the type of improved measurement that such models can provide.

Part 1 examines the most commonly used polytomous IRT models, major issues that cut across these models, and a common notation for calculating functions for each model. An introduction to IRT software is also provided. Part 2 features distinct approaches to evaluating the effectiveness of polytomous IRT models in various measurement contexts. These chapters appraise evaluation procedures and fit tests and demonstrate how to implement these procedures using IRT software. The final section features groundbreaking applications. Here the goal is to provide solutions to technical problems to allow for the most effective use of these models in measuring educational, psychological, and social science abilities and traits. This section also addresses the major issues encountered when using polytomous IRT models in computerized adaptive testing. Equating test scores across different testing contexts is the focus of the last chapter. The various contexts include personality research, motor performance, health and quality of life indicators, attitudes, and educational achievement.

Featuring contributions from the leading authorities, this handbook will appeal to measurement researchers, practitioners, and students who want to apply polytomous IRT models to their own research. It will be of particular interest to education and psychology assessment specialists who develop and use tests and measures in their work, especially researchers in clinical, educational, personality, social, and health psychology. This book also serves as a supplementary text in graduate courses on educational measurement, psychometrics, or item response theory.

Capstone projects have long been used in other disciplines but are now being seen within psychology courses. This textbook is a one-stop-shop for anyone looking to undertake a capstone project or other final project. In a friendly and collaborative style, this book guides the student through everything they need to know to ensure a successful capstone or other final project.

Feminist research is informed by a history of breaking silences, of demanding that women's voices be heard, recorded and included in wider intellectual genealogies and histories. This has led to an emphasis on voice and speaking out in the research endeavour. Moments of secrecy and silence are less often addressed. This gives rise to a number of questions. What are the silences, secrets, omissions and and political consequences of such moments? What particular dilemmas and constraints do they represent or entail? What are their implications for research praxis? Are such moments always indicative of voicelessness or powerlessness? Or may they also constitute a productive moment in the research encounter? Contributors to this volume were invited to reflect on these questions. The resulting chapters are a fascinating collection of insights into the research process, making an important contribution to theoretical and empirical debates about epistemology, subjectivity and identity in research. Researchers often face difficult dilemmas about who to represent and how, what to omit and what to include. This book explores such questions in an important and timely collection of essays from international scholars.

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that basic techniques, routinely taught and used, can perform poorly when dealing with skewed distributions, outliers, heteroscedasticity (unequal variances) and curvature. Methods for dealing with these concerns have been derived and can provide a deeper, more accurate and more nuanced understanding of data. A conceptual basis is provided for understanding when and why standard methods can have poor power and yield misleading measures of effect size. Modern techniques for dealing with known concerns are described and illustrated. Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R Includes an R package with over 1300 functions Includes a solution manual giving detailed answers to all of the exercises This second edition describes many recent advances relevant to basic techniques. For example, a vast array of new and improved methods is now available for dealing with regression, including substantially improved ANCOVA techniques. The coverage of multiple comparison procedures has been expanded and new ANOVA techniques are described. Rand Wilcox is a professor of psychology at the University of Southern California. He is the author of 13 other statistics books and the creator of the R package WRS. He currently serves as an associate editor for five statistics journals. He is a fellow of the Association for Psychological Science and an elected member of the International Statistical Institute.

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.

Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as:

• How missing data affects the statistical power in a study
• How much power is likely with different amounts and types of missing data
• How to increase the power of a design in the presence of missing data, and
• How to identify the most powerful design in the presence of missing data.

Points of Reflection encourage readers to stop and test their understanding of the material. Try Me sections test one s ability to apply the material. Troubleshooting Tips help to prevent commonly encountered problems. Exercises reinforce content and Additional Readings provide sources for delving more deeply into selected topics. Numerous examples demonstrate the book s application to a variety of disciplines. Each issue is accompanied by its potential strengths and shortcomings and examples using a variety of software packages (SAS, SPSS, Stata, LISREL, AMOS, and MPlus). Syntax is provided using a single software program to promote continuity but in each case, parallel syntax using the other packages is presented in appendixes. Routines, data sets, syntax files, and links to student versions of software packages are found at www.psypress.com/davey. The worked examples in Part 2 also provide results from a wider set of estimated models. These tables, and accompanying syntax, can be used to estimate statistical power or required sample size for similar problems under a wide range of conditions.

Class-tested at Temple, Virginia Tech, and Miami University of Ohio, this brief text is an ideal supplement for graduate courses in applied statistics, statistics II, intermediate or advanced statistics, experimental design, structural equation modeling, power analysis, and research methods taught in departments of psychology, human development, education, sociology, nursing, social work, gerontology and other social and health sciences. The book s applied approach will also appeal to researchers in these areas. Sections covering Fundamentals, Applications, and Extensions are designed to take readers from first steps to mastery.

Intended to help improve measurement and data collection methods in the behavioral, social, and medical sciences, this book demonstrates an expanded and accessible use of Generalizability Theory (G theory). G theory conceptually models the way in which the reliability of measurement is ascertained. Sources of score variation are identified as potential contributors to measurement error and taken into account accordingly. The authors demonstrate the powerful potential of G theory by showing how to improve the quality of any kind of measurement, regardless of the discipline.
Readers will appreciate the conversational style used to present a comprehensive review of G theory and its application using the freeware EduG. To maximize understanding the authors illustrate all fundamental principles with concrete examples from different fields and contexts. Annotated applications lead students through the main concepts of G theory, while illustrating both the use of EduG and interpretation of its output. Formulas are avoided wherever possible. Exercises with data sets available on the Psychology Press website allow readers to carry out their own analyses to reinforce understanding.

Brief overviews of analysis of variance, estimation, and the statistical error model are provided for review. The procedures involved in carrying out a generalizability study using EduG follow, as well as guidance in the interpretation of results. Real-world applications of G theory to the assessment of depression, managerial ability, attitudes, and writing and mathematical skills are then presented. Next, annotated exercises provide an opportunity for readers to use EduG and interpret its results. The book concludes with a review of the development of G theory and possible new directions of application. Finally, for those with a strong statistical background, the appendixes provide the formulas used by EduG.

Ideal as a supplement for courses on measurement theory and/or generalizability theory taught in departments of psychology, education, medicine, and the social sciences, this text will also appeal to researchers from a variety of fields interested in learning how to apply G theory to their studies.

This fully updated new edition not only provides an introduction to a range of advanced statistical techniques that are used in psychology, but has been expanded to include new chapters describing methods and examples of particular interest to medical researchers. It takes a very practical approach, aimed at enabling readers to begin using the methods to tackle their own problems.

This book provides a non-mathematical introduction to multivariate methods, with an emphasis on helping the reader gain an intuitive understanding of what each method is for, what it does and how it does it. The first chapter briefly reviews the main concepts of univariate and bivariate methods and provides an overview of the multivariate methods that will be discussed, bringing out the relationships among them, and summarising how to recognise what types of problem each of them may be appropriate for tackling. In the remaining chapters, introductions to the methods and important conceptual points are followed by the presentation of typical applications from psychology and medicine, using examples with fabricated data.

Instructions on how to do the analyses and how to make sense of the results are fully illustrated with dialogue boxes and output tables from SPSS, as well as details of how to interpret and report the output, and extracts of SPSS syntax and code from relevant SAS procedures.

This book gets students started, and prepares them to approach more comprehensive treatments with confidence. This makes it an ideal text for psychology students, medical students and students or academics in any discipline that uses multivariate methods.

Intended to help improve measurement and data collection methods in the behavioral, social, and medical sciences, this book demonstrates an expanded and accessible use of Generalizability Theory (G theory). G theory conceptually models the way in which the reliability of measurement is ascertained. Sources of score variation are identified as potential contributors to measurement error and taken into account accordingly. The authors demonstrate the powerful potential of G theory by showing how to improve the quality of any kind of measurement, regardless of the discipline.
Readers will appreciate the conversational style used to present a comprehensive review of G theory and its application using the freeware EduG. To maximize understanding the authors illustrate all fundamental principles with concrete examples from different fields and contexts. Annotated applications lead students through the main concepts of G theory, while illustrating both the use of EduG and interpretation of its output. Formulas are avoided wherever possible. Exercises with data sets available on the Psychology Press website allow readers to carry out their own analyses to reinforce understanding.

Brief overviews of analysis of variance, estimation, and the statistical error model are provided for review. The procedures involved in carrying out a generalizability study using EduG follow, as well as guidance in the interpretation of results. Real-world applications of G theory to the assessment of depression, managerial ability, attitudes, and writing and mathematical skills are then presented. Next, annotated exercises provide an opportunity for readers to use EduG and interpret its results. The book concludes with a review of the development of G theory and possible new directions of application. Finally, for those with a strong statistical background, the appendixes provide the formulas used by EduG.

Ideal as a supplement for courses on measurement theory and/or generalizability theory taught in departments of psychology, education, medicine, and the social sciences, this text will also appeal to researchers from a variety of fields interested in learning how to apply G theory to their studies.

Surveys are used extensively in psychology, sociology and business, as well as many other areas, but they are becoming increasingly difficult to conduct. Some segments of the population are hard to sample, some are hard to find, others are hard to persuade to participate in surveys, and still others are hard to interview. This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.

Mastering the Semi-Structured Interview and Beyond offers an in-depth and captivating step-by-step guide to the use of semi-structured interviews in qualitative research. By tracing the life of an actual research project-an exploration of a school district's effort over 40 years to address racial equality-as a consistent example threaded across the volume, Anne Galletta shows in concrete terms how readers can approach the planning and execution of their own new research endeavor, and illuminates unexpected real-life challenges they may confront and how to address them. The volume offers a close look at the inductive nature of qualitative research, the use of researcher reflexivity, and the systematic and iterative steps involved in data collection, analysis, and interpretation. It offers guidance on how to develop an interview protocol, including the arrangement of questions and ways to evoke analytically rich data. Particularly useful for those who may be familiar with qualitative research but have not yet conducted a qualitative study, Mastering the Semi-Structured Interview and Beyond will serve both undergraduate and graduate students as well as more advanced scholars seeking to incorporate this key methodological approach into their repertoire.

The development of communication as a discipline has resulted in an explosion of scales tapping various aspects of interpersonal, mass, organizational, and instructional communication. This sourcebook brings together scales that measure a variety of important communication constructs. The scales presented are drawn from areas of interpersonal, mass, organizational, and instructional communication--areas in which the use of formal, quantitative scales is particularly well developed.

Communication Research Measures reflects the recent important emphasis on developing and improving the measurement base of the communication discipline. It results in an equal amount of labor saved on the part of the scholars, students, and practitioners who find this book useful, and it contributes in a significant way to research efforts.
Originally published by Guilford Press in 1994, now available from Routledge.

Successfully used for a number of years by more than four hundred psychologists and psychiatrists, this set of pictures designed to reveal the determinants of psychological conflict is now made available in a standard edition. Thirty halftones printed directly on white cards constitute the new set, and they may be arranged in groups of twenty for boys, for girls, for adult males, and for adult females. A manual of instructions for their use accompanies the pictures. The three previous editions, which were distributed by the Harvard Psychological Clinic, have proved unusually effective in the diagnosis of cases of psychosomatic illness as well as in the neuroses and psychoses.

Albert Einstein said we can't solve problems by using the same kind of thinking we used when we created them. If we don't have the kinds of health and human services or even the kinds of lives, communities and organisations we want, then we need to think differently. Yoland Wadsworth offers an inspired insight and radically new proposition: that the act of our 'inquiring', of researching and evaluating together, is the way by which every living organism and all collective human life goes about continuously achieving the conditions for life. Building in Research and Evaluation explores this new approach for bringing about both wanted change and stability. By inquiring around 'whole cycles' of acting, observing, questioning, feeling, reflecting, thinking, planning and acting again, Yoland identifies how new life might be brought to what we do.

Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton's classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.

Written by an international team of experts, this collection provides a comprehensive account of established and emerging methods of collecting and analysing data within the framework of personal construct theory.

Covers methods such as content analysis scales, repertory grid methodology, narrative assessments and drawings, the laddering and ABC techniques, and discusses how and why they are usedExplores both qualitative and quantitative methods, as well as methods used in clinical and counselling settingsIncludes 13 contributions from leading international scholars

"Testing People at Work" is an authoritative, practical text on selection and assessment. It explains psychometric testing in occupational settings and also covers other methods of selection such as assessment centres and e-selection. The book systematically covers all the topics required for the BPS Certificates of Competence in Testing Levels A and B.
Designed for students taking selection and assessment courses.
Covers the whole process of testing, from job analysis to reporting results.
Uses new theoretical frameworks for the topics of personality and motivation.
Features an extensive discussion of ethics in selection and assessment.
Includes questions testing understanding and suggestions for further reading.
Incorporates many tables and diagrams giving practical help to users of psychometric tests.
Accompanied by supplementary online material, at www.blackwellpublishing.com/testing/.

Brief and inexpensive, this engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Fun interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.

The author s accessible discussion of each misconception has five parts:

• The Misconception - a brief description of the misunderstanding
• Evidence that the Misconception Exists examples and claimed prevalence
• Why the Misconception is Dangerous consequence of having the misunderstanding
• Undoing the Misconception - how to think correctly about the concept
• Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.

The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.

Statistical Misconceptions is appropriate for courses taught in a variety of disciplines including psychology, medicine, education, nursing, business, and the social sciences. The book also will benefit independent researchers interested in undoing their statistical misconceptions. "