This book will help undergraduate psychology students to write practical reports of experimental and other quantitative studies in psychology. It is designed to help with every stage of report writing and provides a resource that students can refer to throughout their degree, up-to and including when writing up a final year undergraduate project. Now fully updated in its fourth edition, this book maps to the seventh edition of the APA guidelines and offers more comprehensive advice, guidelines and recommendations than ever before. Students will benefit from: *Coverage of different forms of quantitative study, including online studies and studies that use questionnaires, as well as experiments *A range of handy test yourself questions (with answers at the end of the book) *Self-reflection questions to prompt deeper understanding *Summary sections that articulate the main points and provide a useful revision aid *An Index of Concepts indicating where in the book every concept is introduced and defined *Updated advice on how to find and cite references *Expanded coverage of ethics in quantitative research, including how to write ethically *Common mistake symbols, flagging areas where its easy to be caught out Peter Harris is Emeritus Professor of Psychology at the University of Sussex, UK where he led the Social and Applied Psychology Group. He has taught research design and statistics for many years. He has published extensively in social and health psychology. Matthew J. Easterbrook is Senior Lecturer in Psychology at the University of Sussex, UK. He has taught statistics at a national and international level. Jessica S. Horst is Reader in Psychology at the University of Sussex, UK, where she is also the Director of Teaching and Learning. She has taught research methods in both the USA and the UK.

Well known for applying mindfulness to the treatment of depression, pioneering researcher John Teasdale now explores the broader changes that people can experience through contemplative practices. What goes on in our minds when we are mindful? What does it mean to talk of mindfulness as a way of being? From a scientific perspective, how do core elements of contemplative traditions have their beneficial effects? Teasdale describes two types of knowing that human beings have evolved--conceptual and holistic-intuitive--and shows how mindfulness can achieve a healthier balance between them. He masterfully describes the mechanisms by which this shift in consciousness not only can reduce emotional suffering, but also can lead to greater joy and compassion and a transformed sense of self.

This book is a seminal guide to loneliness and social isolation in old age, providing a comprehensive overview of the important correlates of socioeconomic, health and lifestyle factors upon loneliness and social isolation in old age. Bringing together contributions from leading authorities, the book showcases expertise from medicine, psychology, epidemiology, sociology, economics and gerontology. It shows the importance of identifying factors associated with loneliness and social isolation among older adults from a broader perspective, and includes discussion of a range of topics including income poverty, physical activity, family care and frailty. The chapters are evidence-based and offer a mix of empirical studies as well as reviews of international research. The book also discusses policy implications and provides an overview of nationally representative cohort studies around the world available to researchers quantifying loneliness or social isolation. This book is unique in examining loneliness and social isolation from such wide-ranging perspectives and will be essential reading for researchers and postgraduate students in the areas of mental health research, social work, and psychiatry. Health professionals involved with gerontology and geriatrics will also find this book of benefit.

Alan C. Acock's A Gentle Introduction to Stata, Revised Sixth Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will be able to not only use Stata well but also learn new aspects of Stata. Acock assumes that the user is not familiar with any statistical software. This assumption of a blank slate is central to the structure and contents of the book. Acock starts with the basics; for example, the part of the book that deals with data management begins with a careful and detailed example of turning survey data on paper into a Stata-ready dataset. When explaining how to go about basic exploratory statistical procedures, Acock includes notes that will help the reader develop good work habits. This mixture of explaining good Stata habits and explaining good statistical habits continues throughout the book. Acock is quite careful to teach the reader all aspects of using Stata. He covers data management, good work habits (including the use of basic do-files), basic exploratory statistics (including graphical displays), and analyses using the standard array of basic statistical tools (correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion). He also successfully introduces some more advanced topics such as multiple imputation and multilevel modeling in a very approachable manner. Acock teaches Stata commands by using the menus and dialog boxes while still stressing the value of Stata commands and do-files. In this way, he ensures that all types of users can build good work habits. Each chapter has exercises that the motivated reader can use to reinforce the material. The tone of the book is friendly and conversational without ever being glib or condescending. Important asides and notes about terminology are set off in boxes, which makes the text easy to read without any convoluted twists or forward referencing. Rather than splitting topics by their Stata implementation, Acock arranges the topics as they would appear in a basic statistics textbook; graphics and postestimation are woven into the material naturally. Real datasets, such as the General Social Surveys from 2002, 2006, and 2016, are used throughout the book. The focus of the book is especially helpful for those in the behavioral and social sciences because the presentation of basic statistical modeling is supplemented with discussions of effect sizes and standardized coefficients. Various selection criteria, such as semipartial correlations, are discussed for model selection. Acock also covers a variety of commands available for evaluating reliability and validity of measurements. The revised sixth edition is fully up to date for Stata 17, including updated discussion and images of Stata's interface and modern command syntax. In addition, examples include new features such as the table command and collect suite for creating and exporting customized tables as well as the option for creating graphs with transparency.

This is the second edition of the comprehensive treatment of statistical inference using permutation techniques. It makes available to practitioners a variety of useful and powerful data analytic tools that rely on very few distributional assumptions. Although many of these procedures have appeared in journal articles, they are not readily available to practitioners. This new and updated edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses.

Beginning-to-end, step-by-step guidance on how to conduct multi-method psychological assessments from a leader in the field The Second Edition of Conducting Psychological Assessment: A Guide for Practitioners delivers an insightful overview of the overall integrative psychological assessment process. Rather than focus on individual tests, accomplished assessment psychologist, professor, and author A. Jordan Wright offers readers a comprehensive roadmap of how to navigate the multi-method psychological assessment process. This newest edition maintains the indispensable foundational models from the first edition and adds nuance and details from the author's last ten years of clinical and academic experience. New ways of integrating and reconciling conflicting data are discussed, as are new models of personality functioning. All readers of this book will benefit from: A primer on the overall process of psychological assessment An explanation of how to integrate the data from the administration, scoring, and interpretation phases into a fully conceptualized report Actual case examples and sample assessment cases that span the entire process Perfect for people in training programs in health service psychology, including clinical, counseling, school, and forensic programs, Conducting Psychological Assessment also belongs on the bookshelves of anyone conducting assessments of human functioning.

Psychological Statistics: The Basics walks the reader through the core logic of statistical inference and provides a solid grounding in the techniques necessary to understand modern statistical methods in the psychological and behavioral sciences. This book is designed to be a readable account of the role of statistics in the psychological sciences. Rather than providing a comprehensive reference for statistical methods, Psychological Statistics: The Basics gives the reader an introduction to the core procedures of estimation and model comparison, both of which form the cornerstone of statistical inference in psychology and related fields. Instead of relying on statistical recipes, the book gives the reader the big picture and provides a seamless transition to more advanced methods, including Bayesian model comparison. Psychological Statistics: The Basics not only serves as an excellent primer for beginners but it is also the perfect refresher for graduate students, early career psychologists, or anyone else interested in seeing the big picture of statistical inference. Concise and conversational, its highly readable tone will engage any reader who wants to learn the basics of psychological statistics.

Behavioral genetics is a fast-growing, multidisciplinary field which attempts to explain the influence of genetic and environmental factors on behavior through the lifespan. The preferred investigative technique for teasing out the differences between genetics and the environment is the longitudinal twin study. This book is the first complete publication from the MacArthur Longitudinal Twin Study (MALTS) that is by far the most ambitious and comprehensive logitudinal twin study to date. The goal of such an in-depth study was merely not to provide thorough descriptions of developmental change between the ages of one and three years, but to offer an original theoretical framework that explains how change occurs in different domains and how genetics and the environment influence those changes. In fact, this rigorous study will set the agenda for developmental psychology and behavioral genetics for decades to come.

This open access book proposes a conceptual framework for understanding measurement across a broad range of scientific fields and areas of application, such as physics, engineering, education, and psychology. It addresses contemporary issues and controversies within measurement in light of the framework, including operationalism, definitional uncertainty, and the relations between measurement and computation, and describes how the framework, operating as a shared concept system, supports understanding measurement’s work in different domains, using examples in the physical and human sciences. This revised and expanded second edition features a new analysis of the analogies and the differences between the error/uncertainty-related approach adopted in physical measurement and the validity-related approach adopted in psychosocial measurement. In addition, it provides a better analysis and presentation of measurement scales, in particular about their relations with quantity units, and introduces the measurand identification/definition as a part of the "Hexagon Framework" along with new examples from the physical and psychosocial sciences. Researchers and academics across a wide range of disciplines including biological, physical, social, and behavioral scientists, as well as specialists in measurement and philosophy appreciate the work’s fresh and provocative approach to the field at a time when sound measurements of complex scientific systems are increasingly essential to solving critical global problems.

This book provides an introduction to and a dynamic description of a new psychological paradigm that balances the excesses and distortions of the positive psychology paradigm. It offers valuable theoretical and practical content to its readers on the vital need for, nature of and potential for the reality psychology paradigm. It includes concrete steps for this new paradigm to restore the real power of vital psychological knowledge and techniques, which need to be brought back from their association with artificial positivity. This will provide real human benefits, including real mindfulness, real resilience, real behaviour change, and real communication. The book features a presentation of the underlying principles of reality psychology - including the value of a full connection with reality as it really is - rather than as we would like it to be. This will help people thrive in response to as well as survive our great real-life challenges, by developing a deeply practical understanding of reality psychology knowledge and related practice techniques. The book provides considerable theoretical and practical benefits to students of a variety of psychological courses, including positive psychology related courses, and also of many other wellbeing related courses. The book also provides valuable benefits to non-student readers - expert and non-expert.

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.

This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. The unifying theme is that supervised learning properly can be seen as a form of regression analysis. Key concepts and procedures are illustrated with a large number of real applications and their associated code in R, with an eye toward practical implications. The growing integration of computer science and statistics is well represented including the occasional, but salient, tensions that result. Throughout, there are links to the big picture. The third edition considers significant advances in recent years, among which are: the development of overarching, conceptual frameworks for statistical learning; the impact of "big data" on statistical learning; the nature and consequences of post-model selection statistical inference; deep learning in various forms; the special challenges to statistical inference posed by statistical learning; the fundamental connections between data collection and data analysis; interdisciplinary ethical and political issues surrounding the application of algorithmic methods in a wide variety of fields, each linked to concerns about transparency, fairness, and accuracy. This edition features new sections on accuracy, transparency, and fairness, as well as a new chapter on deep learning. Precursors to deep learning get an expanded treatment. The connections between fitting and forecasting are considered in greater depth. Discussion of the estimation targets for algorithmic methods is revised and expanded throughout to reflect the latest research. Resampling procedures are emphasized. The material is written for upper undergraduate and graduate students in the social, psychological and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems.

This work brings together different perspectives on psychological methods and particularly methods involving experimentation. To encourage a reflective use of research methods, the authors illuminate the historical, philosophical, and scientific dimensions of methodology, providing both defenses and criticisms of experimental psychology. The primary audience of the work are students and researchers in psychological and behavioral sciences, who have an interest in methodology

This book proposes a novel view to explain how we as humans -- contrary to current robots -- can have the impression of consciously feeling things: for example the red of a sunset, the smell of a rose, the sound of a symphony, or a pain.
The book starts off by looking at visual perception. Our ability to see turns out to be much more mysterious than one might think. The eye contains many defects which should seriously interfere with vision. Yet we have the impression of seeing the world in glorious panavision and technicolor. Explaining how this can be the case leads to a new idea about what seeing really is. Seeing is not passively receiving information in the brain, but rather a way of interacting with the world. The role of the brain is not to create visual sensation, but to enable the necessary interactions with the world.
This new approach to seeing is extended in the second part of the book to encompass the other senses: hearing, touch, taste and smell. Taking sensory experiences to be modes of interacting with the world explains why these experiences are different in the way they are. It also explains why thoughts or automatic functions in the body, and indeed the vast majority brain functions, are not accompanied by any real feeling.
The "sensorimotor" approach is not simply a philosophical argument: It leads to scientifically verifiable predictions and new research directions. Among these are the phenomena of change blindness, sensory substitution, "looked but failed to see," as well as results on color naming and color perception and the localisation of touch on the body.
The approach is relevant to the question of what animals and babies can feel, and to understanding what will be necessary for robots to become conscious.

This is an international and interdisciplinary volume that provides a new look at the general background of the social sciences from a philosophical perspective and provides directions for methodology. It seeks to overcome the limitations of the traditional treatises of a philosophy of science rooted in the physical sciences, as well as extend the coverage of basic science to intentional and socially normative features of the social sciences. The discussions included in this book are divided into four thematic sections: Social and cognitive roots for reflexivity upon the research process Philosophies of explanation in the social sciences Social normativity in social sciences Social processes in particular sciences Social Philosophy of Science for the Social Sciences will find an interested audience in students of the philosophy of science and social sciences. It is also relevant for researchers and students in the fields of psychology, sociology, economics, anthropology, education, and political science.

This proceedings volume highlights the latest research and developments in psychometrics and statistics. It represents selected and peer-reviewed presentations given at the 85th Annual International Meeting of the Psychometric Society (IMPS), held virtually on July 13-17, 2020. The IMPS is one of the largest international meetings on quantitative measurement in education, psychology and the social sciences. It draws approximately 500 participants from around the world, featuring paper and poster presentations, symposiums, workshops, keynotes, and invited presentations. Leading experts and promising young researchers have written the included chapters. The chapters address a wide variety of topics including but not limited to item response theory, adaptive testing, Bayesian estimation, propensity scores, and cognitive diagnostic models. This volume is the 9th in a series of recent works to cover research presented at the IMPS.

This book focuses on the use of the Rasch measurement model in validation studies and in analyzing the psychometric properties of a variety of test instruments, questionnaires, and scales in international contexts. It broadly examines the development and application of Rasch modeling, providing in-depth analyses of the properties of various scales used in the fields of education, and humanities and social sciences research. The book includes exemplary works on educational research and practices that highlight recent and innovative applications, as well as theoretical and practical aspects of Rasch modeling. Readers will find it helpful to understand the latest approaches to Rasch measurement in educational research, as well as practices for future studies and quantitative research. 'This book provides a diverse set of perspectives on Rasch models from scholars across the globe. The volume is both theoretical and applied. The first section of the book provides an overview of Rasch modeling and explains the theoretical and conceptual framework underlying the Rasch model. The remainder of the book highlights multiple applications of the Rasch model within educational assessment as well as several examples of how Rasch modeling can be used for validation studies. This volume showcases the wide variety of ways in which Rasch modeling can be applied to assessment data to provide insights into students' achievement and learning and to improve instruction.'-Betsy McCoach, University of Connecticut, USA. 'A well-written collection of articles. Grouped by the theoretical and applied aspects of Rasch measurement, each chapter in this edited volume makes notable contributions to knowledge and practice. Written by leading scholars in the field, these chapters were written in a clear, succinct, and assertive manner, providing readers with up-to-date information, analyses, and debates. This book should be found in the core collection of emerging researchers and established scholars in educational measurement.'-Timothy Teo, Murdoch University, Australia.

The Generic Qualitative Approach to a Dissertation in the Social Sciences: A Step by Step Guide is a practical guide for the graduate students and faculty planning and executing a generic qualitative dissertation in the social sciences. Generic qualitative research is a methodology that seeks to understand human experience by taking a qualitative stance and using qualitative procedures. Based on Sandra Kostere and Kim Kostere's experiences of serving on dissertation committees, this book aims to demystify both the nuances and the procedures of qualitative research, with the aim of empowering students to conduct meaningful dissertation research and present findings that are rigorous, credible, and trustworthy. It examines the fundamental principles and assumptions underlying the generic qualitative method, then covers each stage of the research process including creation of research questions, interviews, and then offers three ways of analyzing the data gathered and presenting the results. With examples of the generic qualitative method in practice to show students how to conduct their research confidently, and chapters designed to walk the researcher through each step of the dissertation process, this book is specifically tailored for the accessible generic method, and will be useful for graduate students and faculty developing dissertations in Psychology, Education, Nursing and the social sciences.

Interpreting Basic Statistics gives students valuable practice in interpreting statistical reporting as it actually appears in peer-reviewed journals. Features of the ninth edition: * Covers a broad array of basic statistical concepts, including topics drawn from the New Statistics * Up-to-date journal excerpts reflecting contemporary styles in statistical reporting * Strong emphasis on data visualization * Ancillary materials include data sets with almost two hours of accompanying tutorial videos, which will help students and instructors apply lessons from the book to real-life scenarios About this book Each of the 63 exercises in the book contain three central components: 1) an introduction to a statistical concept, 2) a brief excerpt from a published research article that uses the statistical concept, and 3) a set of questions (with answers) that guides students into deeper learning about the concept. The questions on the journal excerpts promote learning by helping students * interpret information in tables and figures, * perform simple calculations to further their interpretations, * critique data-reporting techniques, and * evaluate procedures used to collect data. The questions in each exercise are divided into two parts: (1) Factual Questions and (2) Questions for Discussion. The Factual Questions require careful reading for details, while the discussion questions show that interpreting statistics is more than a mathematical exercise. These questions require students to apply good judgment as well as statistical reasoning in arriving at appropriate interpretations. Each exercise covers a limited number of topics, making it easy to coordinate the exercises with lectures or a traditional statistics textbook.

* Contains two introductory chapters on how to set up an R environment and do basic imports/manipulation of meta-analysis data, including exercises. * Describes statistical concepts clearly and concisely before applying them in R. * Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book.

Advancing work to effectively study, understand, and serve the fastest growing U.S. ethnic minority population, this volume explicitly emphasizes the racial and ethnic diversity within this heterogeneous cultural group. The focus is on the complex historical roots of contemporary Latino/as, their diversity in skin-color and physiognomy, racial identity, ethnic identity, gender differences, immigration patterns, and acculturation. The work highlights how the complexities inherent in the diverse Latino/a experience, as specified throughout the topics covered in this volume, become critical elements of culturally responsive and racially conscious mental health treatment approaches. By addressing the complexities, within-group differences, and racially heterogeneity characteristic of U.S. Latino/as, this volume makes a significant contribution to the literature related to mental health treatments and interventions.

The Social Cognition and Object Relations Scale-Global Rating Method (SCORS-G) is a clinician rated measure that can be used to code various forms of narrative material. It is comprised of eight dimensions which are scored using a seven-point Likert scale, where lower scores are indicative of more pathological aspects of object representations and higher scores are suggestive of more mature and adaptive functioning. The volume is a comprehensive reference on the 1) validity and reliability of the SCORS-G rating system; 2) in depth review of the empirical literature; 3) administration and intricacies of scoring; and 4) the implications and clinical utility of the system across settings and disciplines for clinicians and researchers.

Single-Case Methods in Clinical Psychology: A Practical Guide provides a concise and easily-accessible introduction to single-case research. This is a timely response to the increasing awareness of the need to look beyond randomised controlled trials for evidence to support best practice in applied psychology. The book covers the issues of design, the reliability and validity of measurement, and provides guidance on how to analyse single-case data using both visual and statistical methods. Single-case designs can be used to investigate an individual's response to psychological intervention, as well as to contribute to larger scale research projects. This book illuminates the common principles behind these uses. It describes how standardised measures can be used to evaluate change in an individual and how to develop idiographic measures that are tailored to the needs of an individual. The issue of replication and generalising beyond an individual are examined, and the book also includes a section on the meta-analysis of single-case data. The critical evaluation of single-case research is examined, from both the perspective of developing quality standards to evaluate research and maintaining a critical distance in reviewing one's own work. Single Case Methods in Clinical Psychology will provide invaluable guidance to postgraduate psychologists training to enter the professions of clinical, health and counselling psychology and is likely to become a core text on many courses. It will also appeal to clinicians seeking to answer questions about the effectiveness of therapy in individual cases and who wish to use the method to further the evidence-base for specific psychological interventions.

This book contrasts earlier textbooks on "evidence-based practices." Whereas the latter is a slogan that call for scientific evidence to be used in standardized treatment manuals, ethics-based practices call for individualized treatment that makes the situation meaningful for the patient. The main argument for changing the treatment design from being evidence-based to one based on ethics, is the hypothesis that good health care is based on treatment which makes the situation positive and meaningful for the patient. The awareness for this is primarily provided by ethical considerations.