Awarded the 2019 Most Promising New Textbook Award by the Textbook & Academic Authors Association. This accessible and entertaining new textbook provides students with the knowledge and skills they need to understand the barrage of numbers encountered in their everyday lives and studies. Almost all the statistics in the news, on social media or in scientific reports are based on just a few core concepts, including measurement (ensuring we count the right thing), causation (determining whether one thing causes another) and sampling (using just a few people to understand a whole population). By explaining these concepts in plain language, without complex mathematics, this book prepares students to meet the statistical world head on and to begin their own quantitative research projects. Ideal for students facing statistical research for the first time, or for anyone interested in understanding more about the numbers in the news, this textbook helps students to see beyond the headlines and behind the numbers.

To reflect the importance of supervision and to widen understanding of its many facets, "The Third Eye" brings together contributions from some of the most experienced practitioners of group analysis with the reactions of those they have supervised. The contributors look at questions such as dual supervision, evaluation, block training at home and abroad, training of supervisors and ethical issues. They also give practical advice about maintaining group data, trainee presentations and appraisal techniques. The book concludes with a full reference bibliography of the main articles and books on supervision of group psychotherapy.
This book provides a panoramic exposition by seasoned practitioners of one of the more important but least documented skills demanded in group analysis. However the material extends in relevance beyond its field of origin and will be of significant interest to a wide readership of those concerned with the training, assessment and development of others working with or having responsibility for groups.

The Process of Wellbeing develops an anthropological perspective on wellbeing as an intersubjective process that can be approached through the prism of three complementary conceptual framings: conviviality; care; and creativity. Drawing on ethnographic discussions of these themes in a range of cultural contexts around the world, it shows how anthropological research can help to enlarge and refine understandings of wellbeing, through dialogue with different perspectives and understandings of what it means to live well with others and the skills required to do so. Rather than a state or achievement, wellbeing comes into view here as an ongoing process that involves human and nonhuman others. It does not pertain to the individual alone, but plays out within the relations of care that constitute people, moving and thriving in circulation through affective environments.

A useful handbook, this text presents guidelines frequently followed by writers of reports of empirical research designed for publication in scientific business journals. The guidelines describe the types of information that should be included, how this information should be expressed, and where various types of information should be placed within a report. Excerpts from journal articles are used to illustrate most of the guidelines. At the end of each chapter, there are questions for classroom discussion.

Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book's coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.

Statistical Concepts-A First Course presents the first 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for first and lower-level statistics courses, this book communicates a conceptual, intuitive understanding of statistics that does not assume extensive or recent training in mathematics and only requires a rudimentary knowledge of algebra. Covering the most basic statistical concepts, this book is designed to help readers really understand statistical concepts, in what situations they can be applied, and how to apply them to data. Specifically, the text covers basic descriptive statistics, including ways of representing data graphically, statistical measures that describe a set of data, the normal distribution and other types of standard scores, and an introduction to probability and sampling. The remainder of the text covers various inferential tests, including those involving tests of means (e.g., t tests), proportions, variances, and correlations. Providing accessible and comprehensive coverage of topics suitable for an undergraduate or graduate course in statistics, this book is an invaluable resource for students undertaking an introductory course in statistics in any number of social science and behavioral science disciplines.

How to Structure a Thesis, Report or Paper provides concise practical guidance for students to help make their writing more structured at any level. It assists students in demonstrating what they have learned in the relevant course or degree programme in a way that is accessible to the supervisor and the examiner. Drawing on almost 20 years of supervision experience, the author presents the eight sections of a well-structured thesis, report or paper, together with discussing other relevant issues. Each chapter provides a detailed description of why each section of a thesis, report or paper is structured in the way it is, and its relationship to the whole piece of work. Good and bad examples are provided throughout the book, and there is a focus on key areas such as the six parts of an Introduction and its relationship to the Conclusion, how to phrase clear research questions and hypotheses to the use of references and how to make the thesis, report or paper easier to read. The structure presented in this book can be used to support many courses on the student's entire degree programme, as the structure can be adapted by re-arranging or deleting sections. This book is an invaluable aid to students at all stages in higher education, from their first report or paper until they write their final thesis. It provides clear guidelines for when students should ask their supervisors for advice, and when students can use their own initiative to learn the most. It makes writing a thesis, report or papers more straightforward!

This comprehensive guide offers a rich introduction to research methods, experimental design and data analysis techniques in developmental science, emphasizing the importance of an understanding of this area of psychology for any student or researcher interested in examining development across the lifespan. The expert contributors enhance the reader's knowledge base, understanding of methods, and critical thinking skills in their area of study. They cover development from the prenatal period to adolescence and old age, and explore key topics including the history of developmental research, ethics, animal models, physiological measures, eye-tracking, and computational and robotics models. They accessibly explore research measures and design in topics including gender identity development, the influence of neighborhoods, mother-infant attachment relationships, peer relationships in childhood, prosocial and moral development patterns, developmental psychopathology and social policy, and the examination of memory across the lifespan. Each chapter ends with a summary of innovations in the field over the last ten years, giving students and interested researchers a thorough overview of the field and an idea of what more is to come. Conducting Research in Developmental Psychology is essential reading for upper-level undergraduate or graduate students seeking to understand a new area of developmental science, developmental psychology, and human development. It will also be of interest to junior researchers who would like to enhance their knowledge base in a particular area of developmental science, human development, education, biomedical science, or nursing.

Life Events and Emotional Disorder Revisited explores the variety of events that can occur, their inherent characteristics and how they affect our lives and emotions, and in turn their impact on our mental health and wellbeing. The book focuses on current social problems nationally and internationally, showing the reach of life events research including those linked to Covid-19. It also discusses trauma experiences and how they fit in the life events scheme. To underpin the various life event dimensions identified (such as loss, danger and humiliation), the authors have developed an underlying model of human needs, jeopardised by the most damaging life events. This includes attachment, security, identity and achievement. The book brings together classic research findings with new advances in the field of life events research, culminating in a new theoretical framework of life events, including new discussions on trauma, on positive events and an online methodology for measuring them. Additionally, it draws out the clinical implications to apply the research for improved practice. The book will be of interest to researchers, clinicians and students in psychology, psychiatry and psychotherapy in broadening their understanding of how life events impact on individuals and how this can be applied to enhance clinical practice and stimulate future research.

This Fifth Edition of Neil J. Salkind's Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel, presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Opening with an introduction to Excel, including coverage of how to use functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. New to the Fifth Edition is new co-author Bruce Frey who has added a new feature on statisticians throughout history (with a focus on the contributions of women and people of color). He has updated the "Real-World Stats" feature, and added more on effect sizes, updated the discussions on hypotheses, measurement concepts like validity and reliability, and has more closely tied analytical choices to the level of measurement of variables.

An utterly absorbing collection of ten classic tales from the therapist’s chair by renowned psychiatrist and best-selling author Irvin D. Yalom.

Why was Saul tormented by three unopened letters from Stockholm? What made Thelma spend her whole life raking over a long-past love affair? How did Carlos's macho fantasies help him deal with terminal cancer?

In this engrossing book, Irvin Yalom gives detailed and deeply affecting accounts of his work with these and seven other patients. Deep down, all of them were suffering from the basic human anxieties—isolation, fear of death or freedom, a sense of the meaninglessness of life—that none of us can escape completely. And yet, as the case histories make touchingly clear, it is only by facing such anxieties head on that we can hope to come to terms with them and develop. Throughout, Dr. Yalom remains refreshingly frank about his own errors and prejudices; his book provides a rare glimpse into the consulting room of a master therapist.

Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data. This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including: dichotomous response modeling polytomous response modeling mixed format data modeling concurrent multiple group modeling fixed item parameter calibration modelling with latent regression to include person-level covariate(s) simple structure, or between-item, multidimensional modeling cross-loading, or within-item, multidimensional modeling high-dimensional modeling bifactor modeling testlet modeling two-tier modeling For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.

This new volume reviews longitudinal models and analysis procedures for use in the behavioral and social sciences. Written by distinguished experts in the field, the book presents the most current approaches and theories, and the technical problems that may be encountered along the way. Readers will find new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the research design and the data available. Divided into two parts, Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network analysis and/or growth-curve data. The focus of part two is on the application of longitudinal modeling in a variety of disciplines. The book features applications such as heterogeneity on the patterns of a firm's profit, on house prices, and on delinquent behavior; non-linearity in growth in assessing cognitive aging; measurement error issues in longitudinal research; and distance association for the analysis of change. Part two clearly demonstrates the caution that should be taken when applying longitudinal modeling as well as in the interpretation of the results. Longitudinal Models in the Behavioral and Related Sciences is ideal for advanced students and researchers in psychology, sociology, education, economics, management, medicine, and neuroscience.

Doing Statistical Analysis looks at three kinds of statistical research questions - descriptive, associational, and inferential - and shows students how to conduct statistical analyses and interpret the results. Keeping equations to a minimum, it uses a conversational style and relatable examples such as football, COVID-19, and tourism, to aid understanding. Each chapter contains practice exercises, and a section showing students how to reproduce the statistical results in the book using Stata and SPSS. Digital supplements consist of data sets in Stata, SPSS, and Excel, and a test bank for instructors. Its accessible approach means this is the ideal textbook for undergraduate students across the social and behavioral sciences needing to build their confidence with statistical analysis.

This comprehensive reference organizes extensive definitions and examples of key concepts in quantitative research into a single, convenient source. Alphabetically arranged and cross-referenced, "The Handbook of Research and Quantitative Methods In Psychology" presents:
* experimental procedures,
* research designs,
* statistical methods,
* information theory,
* psychophysics,
* behavioral terminology,
* scaling and testing.

*Comprehensive, accessible text, updated: 40% new material includes a new chapter on multilevel IRT models, new material on loglinear models, and more. *Shows how to apply IRT by using common datasets across chapters. *Companion website provides datasets, software links, and additional resources. *Works through the examples using both free and commercially available software programs. *Of particular interest in the U.S., the U.K., Scandinavia, the Netherlands, Germany, China, and Korea.

This groundbreaking edited book, The Routledge Handbook for Advancing Integration in Mixed Methods Research, presents an array of different integration ideas, with contributions from scholars across the globe. This handbook represents the first major volume that comprehensively discusses this topic of integration. Perhaps the most fundamental and longstanding question in mixed methods research is: How does one best integrate disparate forms of information to produce the best form of inquiry? Each of the 34 seminal chapters in this handbook accelerates the discussion of integration across a broad range of disciplines, including education, arts-based analyses, and work in the Global South, as well as special topics such as psychometrics and media research. Many of the chapters present new topics that have never been written about before, and all chapters offer cutting-edge approaches to integration. They also offer different perspectives of integration - leading the introductory chapter to offer a new and comprehensive definition for integration, as follows: "referring to the optimal mixing, combining, blending, amalgamating, incorporating, joining, linking, merging, consolidating, or unifying of research approaches, methodologies, philosophies, methods, techniques, concepts, language, modes, disciplines, fields, and/or teams within a single study." The concluding chapter offers a meta-framework that accounts for this definition and is designed to help scholars think more about integration in a way that represents a continuous, dynamic, iterative, interactive, synergistic, and holistic meaning-making process. This handbook will be an essential reference work for all scholars and practitioners using or seeking to use mixed methods in their research.

Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.

Killer Data examines the phenomenon of serial murder using data collected from international sources to review offender patterning with a focus on contemporary cases. This type of attention will allow for a broader understanding of modern-day serial murderers and will help to dispel some of the myths that surround offenders.

　The current serial murder classification scheme incorrectly types serial murderers as supremely intelligent killing machines while discounting their socialization, experiences, and choices. This book exposes serial murderers as run-of-the-mill hometown losers, who brutalize women, and are lucky to escape apprehension. Like other atypical homicide offenders, modern-day serial murderers are propelled forward by a deep sense of entitlement, easy access to firearms, and a nonchalant attitude toward using murder to attain their goals. Readers should come away with a deeper understanding not of the ultra-rare or the "deadliest" serial murderers but of the more common offenders who pose a consistent threat to day-to-day life. The book utilizes the Consolidated Serial Homicide Offender Database, one of the largest and most robust open access databases of multiple murders available, presenting new thinking on areas such as:

myths and stereotypes

the impact of entertainment on the perception of serial murder

inaccurate prevalence estimates

spree/serial hybrid offenders

the classification of two and three victim serial murderers

how serial murderers pursue longevity

the characteristics of aspiring serial murderers

whether hit men and gang members are serial murderers

if and why serial murder is in a state of decline

how many serial murderers are responsible for the homicides that sent innocent people to prison

luck as a factor of “success” for serial murderers.

These findings are illustrated with 200 narrative vignettes of serial murder series that occurred between 2011 and 2021, such as Itzcoatl Ocampo, Charles Severance, Nikko Jenkins, and Pamela Hupp, offenders who may be unfamiliar to many but represent the next iteration of the serial murderer.

　Correcting decades of flawed assumptions about serial murderers, and written in an accessible and concise style, Killer Data is essential reading for students and scholars of criminal justice and criminology, law enforcement professionals, and the interested general reader.

Table of Contents

List of Tables

List of Figures

Foreword

Preface

Acknowledgments

1: Serial Murder: Then and Now

Introduction

2: What Do We Know About Serial Murder and How Do We Know It?

3: Serial Murder: 2011 – 2021

4: An Overview of the Modern Serial Murderer

5: Concluding Thoughts

Index/

*Unique and authoritative: the first-ever volume on the use of computational language analysis in psychological research. *Needed guide: new ways to use language analysis to explore foundational psychological questions are growing exponentially. *Interdisciplinary: these methods are also relevant to linguistics, communication, information sciences, and business. *From leading editors and contributors.

Neuropsychology for Occupational Therapists is a bestselling, comprehensive guide to the assessment and rehabilitation of impaired cognitive function and brain damage. Divided into two parts, the first introduces the fundamental role cognition has in occupational performance, before moving on to examine the theoretical frameworks behind cognitive rehabilitation. The second part covers the key components of each cognitive function, including attention, visual perception, movement, memory, and executive functions, and the disorders associated with them. Revised throughout, this invaluable new edition includes: * Updated theory and evidence base of neuropsychology * Frameworks and guidelines for assessment and intervention in practice * Updated content on attention, memory and executive functions * A new chapter on cognitive function in later years, and working with people to maintain cognitive health. Written in a clear and engaging style by an experienced author team of academic occupational therapists, with contributions from expert practising clinicians, it is full of a range of learning features, including case studies, summaries, and reflective activities, as well as for the first time narratives of the lived experience of cognitive impairment. Neuropsychology for Occupational Therapists is essential reading for students, newly qualified practitioners, and all those who work within neuropsychology and cognitive rehabilitation.

It is universally accepted that sensitive and responsive caregiving leads to positive cognitive and socio-emotional outcomes for children. While several intervention approaches exist, this text brings together the rationale and current evidence base for one such approach-the Mediational Intervention for Sensitizing Caregivers (MISC). MISC integrates aspects of socio-emotional health and cognitive development as well as being less culturally intrusive than existing approaches. It is a strengths-based program complementing existing practices and cultures. Editors bring together in one volume the theory and research from the last decade supporting the MISC approach. Chapters focus on a range of topics, such as training the trainer, maternal depression and MISC, applying MISC to families reunited after migration-related separation and more. The book also focuses on several country-specific cases, such as applying MISC to HIV/AIDS-affected children in South Africa or in early childhood care settings in Israel. This book is essential reading for those working in early educational or clinical settings tasked with developing policy to ensure optimal child developmental outcomes. The book is applicable to professionals from a wide variety of disciplines including clinical, counselling, educational, psychology, psychiatry, paediatrics, nursing, social work and public health.

Leading therapists and researchers have come to understand that many psychological disorders share common features and respond to common therapeutic treatments. This deepened understanding of the nature of psychological disorders, their causes, and their symptoms has led to the development of new, comprehensive treatment programs that are effective for whole classes of disorders. Unified Protocol for Transdiagnostic Treatment of Emotional Disorders is one such program. Designed for individuals suffering from emotional disorders, including panic disorder, social anxiety disorder, generalized anxiety disorder, posttraumatic stress disorder, obsessive compulsive disorder, and depression, this program focuses on helping you to better understand your emotions and identify what you're doing in your responses to them that may be making things worse. Throughout the course of treatment you will learn different strategies and techniques for managing your emotional experiences and the symptoms of your disorder. You will learn how to monitor your feelings, thoughts, and behaviors; confront uncomfortable emotions; and learn more effective ways of coping with your experiences. By proactively practicing the skills presented in this book-and completing the exercises, homework assignments and self-assessment quizzes provided in each chapter, you will address your problems in a comprehensive and effective way so you can regulate your emotional experiences and return to living a happy and functional life.

In the eleventh edition of Understanding Research Methods: An Overview of the Essentials, Newhart and Patten leverage the principles of learning and content design to present the fundamentals students need to get started in research. Basics of quantitative and qualitative research are covered in short, independent topics and grouped into meaningful sections.

A perennial bestseller for over ten editions, Understanding Research Methods focuses concisely on key concepts, and lessons in topics that are "chunked" to suit today’s students. Each topic ends with suggestions for planning a research project by answering topic-specific prompts in a research planning journal. Topic Review exercises encourage active learning. Finally, Topics for Discussion suggest open-ended prompts that could serve as conversation starters in the classroom or online. The final Part of the book offers guidance and activities specific to writing a research report. This section can be used to support the development of project-based assignments for courses, or it can be used independently to support senior thesis projects, master’s theses, dissertations, or articles for publication.

Instructors, will appreciate the organization of Understanding Research Methods because it allows a great deal of customization and choice in which topics to cover and in what order to cover them, making it suitable for methodological training in a variety of courses and fields of study. Online digital materials support course development.

New to this edition:

Part introductions now include a part table of contents and list of keywords

Newly expanded coverage of qualitative research

New coverage on designing quantitative research

Expanded material on sampling

More simple graphs, charts, and illustrations emphasize and visualize Topic key points

Table of Contents

1. Introduction to Research Methods 2. Reading, Reviewing, and Citing Literature 3. Basic Concepts in Quantitative Research 4. Designing Quantitative Research 5. Assessing Research Quality: Validity and Reliability 6. Sampling for Quantitative Research 7. Analyzing Quantitative Data 8. Qualitative Research 9. Writing About Research

* It is a straightforward, conversational introduction to statistics that delivers exactly what its title promises. * Each chapter begins with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides. * Chapters also include an example of the statistic (or statistics) in use in real-world research, "Worked Examples," "Writing It Up" sections that demonstrate how to write about each statistic, "Wrapping Up and Looking Forward" sections, and practice work problems. * A new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added (Chapter 16). * Person-centered analysis is an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression) and is gaining popularity in social-science research. * The chapter on non-parametric statistics (Chapter 14) was enhanced significantly with in-depth descriptions of Mann-Whitney U, Kruskall-Wallace, and Wilcoxon Signed-Rank analyses. * These non-parametric statistics are important alternatives to statistics that rely on normally distributed data. * This new edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression (Chapter 13). * There is more information provided about the importance of the normal distribution in statistics (Chapters 4 and 7). * Each of the last nine chapters includes an example from the real world of research that employs the statistic, or statistics, covered in the chapter. * Altogether, these improvements provide important foundational information about how inferential statistics work and additional statistical tools that are commonly used by researchers in the social sciences. * The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.