Experimental design is important enough to merit a book on its own, without statistics, that instead links methodology to a discussion of how psychologists can advance and reject theories about human behaviour. The objective of this book is to fulfil this role.; The first four chapters lay the foundations of design in experimental psychology. The first chapter justifies the prominent role given to methodology within the discipline, whilst chapters two and three describe between-subject and within-subject designs. Chapter four compares and contrasts the traditional experimental approach with that of the quasi-experimental, or correlational approach, concluding that the consequences of not recognizing the value of the latter approach can be far-reaching.; The following three chapters discuss practical issues involved in running experiments. The first of these offers a comprehensive guide to the student researcher who wants to construct a good questionnaire, including a discussion of reliability and validity issues. The next chapter considers the basic tools of psychological research, whilst both discussing the theoretical problem of how a sample from a population is chosen and offering useful hints on the practical issue of finding adequate populations from which to select participants. The next chapter considers ethical practice within psychological research, written in large part so that psychology students will be better able to anticipate ethical problems in their studies before they occur.; The final two chapters consider reporting and reading psychological papers. Chapter eight details what should and should not be included in a laboratory report. The contributors use their collective experience of marking numerous lab reports to highlight common errors and provide solutions. Finally, chapter nine describes the various elements of a journal article, including tips on how to get the best out of your journal reading.

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Experimental design is important enough to merit a book on its own, without statistics, that instead links methodology to a discussion of how psychologists can advance and reject theories about human behaviour. The objective of this book is to fulfil this role. The first four chapters lay the foundations of design in experimental psychology. The first chapter justifies the prominent role given to methodology within the discipline, whilst chapters two and three describe between-subject and within-subject designs. Chapter four compares and contrasts the traditional experimental approach with that of the quasi-experimental, or correlational approach, concluding that the consequences of not recognizing the value of the latter approach can be far-reaching. The following three chapters discuss practical issues involved in running experiments. The first of these offers a comprehensive guide to the student researcher who wants to construct a good questionnaire, including a discussion of reliability and validity issues. The next chapter considers the basic tools of psychological research, whilst both discussing the theoretical problem of how a sample from a population is chosen and offering useful hints on the practical issue of finding adequate populations from which to select participants. The next chapter considers ethical practice within psychological research, written in large part so that psychology students will be better able to anticipate ethical problems in their studies before they occur. The final two chapters consider reporting and reading psychological papers. Chapter eight details what should and should not be included in a laboratory report. The contributors use their collective experience of marking numerous lab reports to highlight common errors and provide solutions. Finally, chapter nine describes the various elements of a journal article, including tips on how to get the best out of your journal reading.

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Taking philosophical principles as a point of departure, this book provides essential distinctions for thinking through the history and systems of Western psychology. The book is concisely designed to help readers navigate through the length and complexity found in history of psychology textbooks. From Plato to beyond Post-Modernism, the author examines the choices and commitments made by theorists and practitioners of psychology and discusses the philosophical thinking from which they stem. What kind of science is psychology? Is structure, function, or methodology foremost in determining psychology's subject matter? Psychology, as the behaviorist views it, is not the same as the psychoanalyst's view of it, or the existentialist's, so how may contemporary psychology philosophically-sustain both pluralism and incommensurability? This book will be of great value to students and scholars of the history of psychology.

Provides researchers with a reproducible research workflow for using R/RStudio to make the entire researchprocess reproducible; from data gathering, to analysis, to presentation Includes instructions not only for creating reproducible research in R, but also extensively discusses how to take advantage of recent developments in RStudio. Emphasizes the presentation of reproducible research with non-print formats such as HTML5 slideshows, blogs, and other web-based content. Covers a range of techniques to organize and remotely store files at all stages of the research process. These techniques both streamline the research process, especially by making revisions easier, and enhance The book itself will be reproducible, as all of the data, analysis, and markup files will be made available online.

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.

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!

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.

This book is not available as a print inspection copy. To download an E-inspection copy click here or for more information contact your local sales representative. Taking you through each aspect of the research process and explaining the unique challenges of using qualitative methods in psychology, this book offers a complete guide to successfully conducting a qualitative psychological research project. Clear, concise and accessible, this 'how to' manual folds key skills like research design and using technology and software into each chapter. This second edition offers: - A thorough introduction to foundational concepts that support you through each step of the research process - New chapters on thematic and narrative analysis - A set of digital resources designed to make learning about qualitative methods as easy and interactive as possible, including video recordings and transcripts to build key analysis techniques Through a pragmatic, practical lens, this book provides the perspective and the tools you need to recognize, collect, interpret, and communicate quality qualitative psychological data. Michael A. Forrester is a Senior Lecturer in Psychology at the University of Kent, Canterbury. Cath Sullivan is a Senior Lecturer in the School of Psychology at the University of Central Lancashire.

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.

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.

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.

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.

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.

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 accessible, practical introduction to carrying out qualitative research in psychotherapy and counselling for practitioners who want or who are required to contribute to the profession's evidence base. Gives clear guidance on how to set up and conduct small scale research that is based in clinical practice Assumes no prior knowledge of qualitative research and is aimed specifically at psychotherapists Recognises development of the evidence base for psychotherapy through qualitative research as a key objective for practitioners

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.

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.

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/

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.

W. W. Norton is excited to announce that award-winning authors Elizabeth Phelps and Elliot Berkman will bring their ideas and energy to Psychological Science 7e. Our authors are committed to encouraging students to learn and evaluate psychology through the lens of methods, replication and the open science era. Looking beyond the text, Liz and Elliot applied their experience with the introductory psychology course to all aspects of the teaching and learning tools, including InQuizitive's adaptive assessment, new ZAPS 3.0 interactive labs with instructor support, a hands-on approach to visualising brain science through a new interactive 3D brain and exciting new interactive neuron animations. They are committed to introducing students to a more modern view of the field-one that shows the real-world impact of psychology and showcases the work of diverse researchers throughout.

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.

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

Discursive Psychology is a theoretical and analytical approach used by academics and practitioners alike, widely applied, though often lost within the complicated web of discourse analysis. Sally Wiggins combines her expertise in discursive psychology with her clear and demystifying pedagogical approach to produce a book that is committed to student success. This textbook shows students how to put the methodology into practice in a way that is simple, engaging and practical.

Offers a unified discussion of generalized linear models and correlated data methods Provides information suitable for graduate non-statistics majors or advanced undergraduate statistics majors Includes case studies with real data Offers material on R at the end of each chapter Provides a solutions manual

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.