This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568.

The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced.

Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors' highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.

Behavioral scientists - including those in psychology, infant and child development, education, animal behavior, marketing and usability studies - use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers and assessing reliability, as well as recording, representing and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis, including both statistical and graphical means.

Psychoanalytic infant observation is frequently used in training psychoanalytic psychotherapists and allied professionals, but increasingly its value as a research method is being recognised, particularly in understanding developmental processes in vulnerable individuals and groups. This book explores the scope of this approach and discusses its strengths and limitations from a methodological and philosophical point of view.

Infant Observation and Research uses detailed case studies to demonstrate the research potential of the infant observation method. Divided into three sections this book covers

• infant observation as part of the learning process
• how infant observation can inform understanding and influence practice
• psychoanalytic infant observation and other methodologies.

Throughout the book, Cathy Urwin, Janine Sternberg and their contributors introduce the reader to the nature and value of psychoanalytic infant observation and its range of application. This book will therefore interest a range of mental health practitioners concerned with early development and infants' emotional relationships, as well as academics and researchers in the social sciences and humanities.

This volume provides an integrative review of the emerging and increasing use of network science techniques in cognitive psychology, first developed in mathematics, computer science, sociology, and physics. The first resource on network science for cognitive psychologists in a growing international market, Vitevitch and a team of expert contributors provide a comprehensive and accessible overview of this cutting-edge topic. This innovative guide draws on the three traditional pillars of cognitive psychological research-experimental, computational, and neuroscientific-and incorporates the latest findings from neuroimaging. The network perspective is applied to the fundamental domains of cognitive psychology including memory, language, problem-solving, and learning, as well as creativity and human intelligence, highlighting the insights to be gained through applying network science to a wide range of approaches and topics in cognitive psychology Network Science in Cognitive Psychology will be essential reading for all upper-level cognitive psychology students, psychological researchers interested in using network science in their work, and network scientists interested in investigating questions related to cognition. It will also be useful for early career researchers and students in methodology and related courses.

Presenting an innovative take on researching early childhood, this book provides an international comparison of the cultural and familial influences that shape the growth of young children. The book presents a unique methodology, and includes chapters on musicality, security, humour and eating.

The Handbook of Psychodiagnostic Testing is an invaluable aid to students and professionals performing psychological assessments. It takes the reader from client referral to finished report, demonstrating how to synthesize details of personality and pathology into a document that is focused, coherent, and clinically meaningful.

This new edition covers emerging areas in borderline and narcissistic pathologies, psychological testing of preschool children, and bilingual populations. It also discusses the most current clinical issues and evaluating populations on which standard psychological tests have not been standardized.

Synthesizing many years' investigation into sexual identity and orientation, this book presents Dr Money's formulation of how sexual preference is determined. It includes a review of long-term follow-up studies on pre-natal influences on sexual identity, and discusses gender differentiation in childhood. The book concludes with an examination of the conflict between gender and sexual identities, and a description of the paraphilias.

Researchers, clinicians, and graduate students in psychology, biology, endocrinology, psychiatry, and family studies will find this volume of interest, as will anyone interested in gay and lesbian issues.

Qualitative methodologies in cultural psychology often lack the objective and verifiable character of quantitative analysis. Author Carl Ratner corrects this shortcoming by rigorously systematizing qualitative methods. The book discusses, for example, means of systematizing such subjective reports as interviews, letters, and diaries, which often yield valuable data that is not easily quantified. Ratner argues that "complex psychological phenomena are expressed through extended responses" and hence are best studied by new, more regularized qualitative methods that go beyond measuring simple, overt responses.

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.

This book explores how an object relations--integrative perspective may combine in--depth psychodynamic principles and theories with the flexibility afforded by an integrative framework. Object relations theory is rooted in a psychoanalytic tradition which views individuals essentially social and holds that their need for others is primary. Integrative psychotherapy attempts to combine the theories and/or techniques of two or more therapeutic approaches. This volume is useful for graduates, undergraduates and trainee psychotherapists as well as social workers, psychologists, psychotherapists and counsellors who are interested in broadening their understanding of different therapeutic approaches and intefrative endeavours. The contributors consist of an international group of practitioners and theoreticians who draw on the knowlege of object realtions and other therapeutic orientations as well as innovations in the integrative movement. Some of te contributors grapple directly with integrative questions, while others examine ways of working with specific client groups or methods, where integrative ideas enrich their work.

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

Shame remains at the core of much psychological distress and can eventuate as physical symptoms, yet experiential approaches to healing shame are sparse. Links between shame and art making have been felt, intuited, and examined, but have not been sufficiently documented by depth psychologists. Shame and the Making of Art addresses this lacuna by surveying depth psychological conceptions of shame, art, and the role of creativity in healing, contemporary and historical shame ideologies, as well as recent psychobiological studies on shame. Drawing on research conducted with participants in three different countries, the book includes candid discussions of shame experiences. These experiences are accompanied by Cluff's heuristic inquiry into shame with an interpretative phenomenological analysis that focuses on how participants negotiate the relationship between shame and the making of art. Cluff's movement through archetypal dimensions, especially Dionysian, is developed and discussed throughout the book. The results of the research are further explicated in terms of comparative studies, wherein the psychological processes and impacts observed by other researchers and effects on self-conscious maladaptive emotions are described. Shame and the Making of Art should be essential reading for academics, researchers, and postgraduate students engaged in the study of psychology and the arts. It will be of particular interest to psychologists, Jungian psychotherapists, psychiatrists, social workers, creativity researchers, and anyone interested in understanding the dynamics of this shame and self-expression.

What drives people toward their goals? Does motivation come from outside the individual or from within? This is a concise, engaging overview of leading theories and the wide body of research about this core concept in psychology. It draws from a broad spectrum of psychological models and disciplines, and focuses on how various theories of motivation define and examine different motivational attributes, such as rewards and goals. Real life case examples illuminate how various models explain behavior and connect the study of motivation to our daily lives.

An entertaining, affordable alternative to lengthy and expensive texts on the subject, Motivation 101 is unique in helping readers understand how each theory of motivation-behavioral, neurobiological, attribution, and other paradigms--views and defines a particular concept within the model. For example, each modality views the concept of "reward" from a different perspective. Tables within each chapter compare and contrast the thinking of different schools in regard to each construct. The book is also unique in its multidisciplinary focus, whereby research is drawn not only from different domains of psychology but also from such disciplines as education and business. The book considers cultural differences in the study of motivation and collaborative environments, and addresses changing research methodologies. The book concludes with a discussion of how motivation theory is applied in practical contexts to create change in the world. It will be an asset to undergraduate and graduate courses in motivation in psychology, education, and business.

Key Features: Provides a concise, engaging overview of motivation that encompasses leading theories and a broad body of research Compares and contrasts different schools of motivation theories and models including needs-based and cognitively based paradigms Draws from research across a wide range of domains within psychology, education, and business Connects the study of motivation to our daily lives through case examples and metaphors Demonstrates how applying theories of motivation can have tremendous impact on behavior change

How does mindfulness promote psychological well-being? What are its core mechanisms? What value do contemplative practices add to approaches that are already effective? From leading meditation teacher Christina Feldman and distinguished psychologist Willem Kuyken, this book provides a uniquely integrative perspective on mindfulness and its applications. The authors explore mindfulness from its roots in Buddhist psychology to its role in contemporary psychological science. In-depth case examples illustrate how and why mindfulness training can help people move from distress and suffering to resilience and flourishing. Readers are guided to consider mindfulness not only conceptually, but also experientially, through their own journey of mindfulness practice.

The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.

A Handbook of Process Tracing Methods demonstrates how to better understand decision outcomes by studying decision processes, through the introduction of a number of exciting techniques. Decades of research have identified numerous idiosyncrasies in human decision behavior, but some of the most recent advances in the scientific study of decision making involve the development of sophisticated methods for understanding decision process-known as process tracing. In this volume, leading experts discuss the application of these methods and focus on the best practices for using some of the more popular techniques, discussing how to incorporate them into formal decision models. This edition has been expanded and thoroughly updated throughout, and now includes new chapters on mouse tracking, protocol analysis, neurocognitive methods, the measurement of valuation, as well as an overview of important software packages. The volume not only surveys cutting-edge research to illustrate the great variety in process tracing techniques, but also serves as a tutorial for how the novice researcher might implement these methods. A Handbook of Process Tracing Methods will be an essential read for all students and researchers of decision making.

Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements. The book looks at the process of empirical research into the following seven stages: * Formulation of the problem * Stipulation of the precision requirements * Selecting the statistical model for the planning and analysis * The (optimal) design of the experiment or survey * Performing the experiment or the survey * Statistical analysis of the observed results * Interpretation of the results.

This volume, Statistical Methods in Psychiatry Research and SPSS, now going into its second edition, has been helping psychiatrists expand their knowledge of statistical methods and fills the gaps in their applications as well as introduces data analysis software. It addresses the statistical needs of physicians and presents a simplified approach. The book emphasizes the classification of fundamental statistical methods in psychiatry research that are precise and simple. Professionals in the field of mental health and allied subjects without any mathematical background will easily understand all the relevant statistical methods and carry out the analysis and interpret the results in their respective field without consulting any statistician. This new volume has over 100 pages of new material, including several new appendixes. The sequence of the chapters, the sections within the chapters, the subsections within the sections, and the points within the subsections have all been arranged to help professionals in classification refine their knowledge in statistical methods and fills the gaps.

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these "methodological urban legends," as we refer to them in this book, are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can t generalize these findings to the real world"; or (d) "your effect sizes are too low."

Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: (a) what the legend is that "we (almost) all know to be true"; (b) what the "kernel of truth" is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.

This guide reveals the best ways for students to analyse data and interpret results in SPSS. Georjeanna Wilson-Doenges's direct writing style, real sample data from her research methods class, integrated APA-style results, and detailed yet clear screenshots ensure that students feel confident using the programme. Her exciting revision not only reflects the latest updates to SPSS and APA guidelines but also includes new engaging step-by-step video tutorials.

This book is a practical resource designed for clinicians, researchers, and advanced students who wish to learn about single-case research designs. It covers the theoretical and methodological underpinnings of single-case designs, as well as their practical application in the clinical and research neurorehabilitation setting. The book briefly traces the history of single-case experimental designs (SCEDs); outlines important considerations in understanding and planning a scientifically rigorous single-case study, including internal and external validity; describes prototypical single-case designs (withdrawal-reversal designs and the medical N-of-1 trial, multiple-baseline designs, alternating-treatments designs, and changing-criterion designs) and required features to meet evidence standards, threats to internal validity, and strategies to address them; addresses data evaluation, covering visual analysis of graphed data, statistical techniques, and clinical significance; and provides a practical ten-step procedure for implementing single-case methods. Each chapter includes detailed illustrative examples from the neurorehabilitation literature. Novel features include: A focus on the neurorehabilitation setting, which is particularly suitable for single-case designs because of the complex and often unique presentation of many patients/clients. A practical approach to the planning, implementation, data analysis, and reporting of single-case designs. An appendix providing a detailed summary of many recently published SCEDs in representative domains in the neurorehabilitation field, covering basic and instrumental activities of daily living, challenging behaviours, disorders of communication and cognition, mood and emotional functions, and motor-sensory disabilities. It is valuable reading for clinicians and researchers in several disciplines working in rehabilitation, including clinical and neuropsychology, education, language and speech pathology, occupational therapy, and physical therapy. It is also an essential resource for advanced students in these fields who need a textbook for specialised courses on research methodology and use of single-case design in applied clinical and research settings.

Although best known for experimental methods, social psychology also has a strong tradition of measurement. This volume seeks to highlight this tradition by introducing readers to measurement strategies that help drive social psychological research and theory development. The books opens with an analysis of the measurement technique that dominates most of the social sciences, self-report. Chapter 1 presents a conceptual framework for interpreting the data generated from self-report, which it uses to provide practical advice on writing strong and structured self-report items. From there, attention is drawn to the many other innovative measurement and data-collection techniques that have helped expand the range of theories social psychologists test. Chapters 2 through 6 introduce techniques designed to measure the internal psychological states of individual respondents, with strategies that can stand alone or complement anything obtained via self-report. Included are chapters on implicit, elicitation, and diary approaches to collecting response data from participants, as well as neurological and psychobiological approaches to inferring underlying mechanisms. The remaining chapters introduce creative data-collection techniques, focusing particular attention on the rich forms of data humans often leave behind. Included are chapters on textual analysis, archival analysis, geocoding, and social media harvesting. The many methods covered in this book complement one another, such that the full volume provides researchers with a powerful toolset to help them better explore what is "social" about human behavior.

This volume presents a collection of chapters focused on the study of multivariate change. As people develop and change, multivariate measurement of that change and analysis of those measures can illuminate the regularities in the trajectories of individual development, as well as time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social sciences, models of change have become increasingly important. This collection focuses on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes. The volume is divided into three major sections: Extension of latent change models, Measurement and testing issues in longitudinal modeling, and Novel applications of multivariate longitudinal methodology. It is intended for advanced students and researchers interested in learning about state-of-the-art techniques for longitudinal data analysis, as well as understanding the history and development of such techniques.

Outcome Research and the Future of Psychoanalysis explores the connection between outcome studies and important and complex questions of clinical practices, research methodologies, epistemology, and sociological considerations. Presenting the ideas and voices of leading experts in clinical and extra-clinical research in psychoanalysis, the book provides an overview of the state of the art of outcome research, its results and implications. Furthermore, its contributions discuss the basic premises and ideas of outcome research and in which way the contemporary Zeitgeist might shape the future of psychoanalysis. Divided into three parts, the book begins by discussing the scientific basis of psychoanalysis and advances in psychoanalytic thinking as well as the state of the art of psychoanalytic outcome research, critically analyzing so-called evidence-based therapies. Part II of the book contains exemplary research projects that are discussed from a clinical perspective, illustrating the dialogue between researchers and clinicians. Lastly, in Part III, several psychoanalysts review the importance of critical thinking and research in psychoanalytical education. Thought-provoking and expertly written and researched, this book is a useful resource for academics, researchers and postgraduate students in the fields of mental health, psychotherapy, and psychoanalysis.