Power Analysis of Trials with Multilevel Data covers using power and sample size calculations to design trials that involve nested data structures. The book gives a thorough overview of power analysis that details terminology and notation, outlines key concepts of statistical power and power analysis, and explains why they are necessary in trial design. It guides you in performing power calculations with hierarchical data, which enables more effective trial design. The authors are leading experts in the field who recognize that power analysis has attracted attention from applied statisticians in social, behavioral, medical, and health science. Their book supplies formulae that allow statisticians and researchers in these fields to perform calculations that enable them to plan cost-efficient trials. The formulae can also be applied to other sciences. Using power analysis in trial design is increasingly important in a scientific community where experimentation is often expensive, competition for funding among researchers is intense, and agencies that finance research require proposals to give thorough justification for funding. This handbook shows how power analysis shapes trial designs that have high statistical power and low cost, using real-life examples. The book covers multiple types of trials, including cluster randomized trials, multisite trials, individually randomized group treatment trials, and longitudinal intervention studies. It also offers insight on choosing which trial is best suited to a given project. Power Analysis of Trials with Multilevel Data helps you craft an optimal research design and anticipate the necessary sample size of data to collect to give your research maximum effectiveness and efficiency.

Praise for the first edition: "One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff-inferential statistics. The author manages to do this very quickly....if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software [this text] fits the bill." -The American Statistician Applied Statistical Inference with MINITAB, Second Edition distinguishes itself from other introductory statistics textbooks by focusing on the applications of statistics without compromising mathematical rigor. It presents the material in a seamless step-by-step approach so that readers are first introduced to a topic, given the details of the underlying mathematical foundations along with a detailed description of how to interpret the findings, and are shown how to use the statistical software program Minitab to perform the same analysis. Gives readers a solid foundation in how to apply many different statistical methods. MINITAB is fully integrated throughout the text. Includes fully worked out examples so students can easily follow the calculations. Presents many new topics such as one- and two-sample variances, one- and two-sample Poisson rates, and more nonparametric statistics. Features mostly new exercises as well as the addition of Best Practices sections that describe some common pitfalls and provide some practical advice on statistical inference. This book is written to be user-friendly for students and practitioners who are not experts in statistics, but who want to gain a solid understanding of basic statistical inference. This book is oriented towards the practical use of statistics. The examples, discussions, and exercises are based on data and scenarios that are common to students in their everyday lives.

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.

This book has been prepared to help psychiatrists expand their knowledge of statistical methods and fills the gaps in their applications as well as introduces data analysis software. 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 can easily understand all the relevant statistical methods and carry out the analysis and interpret the results in their respective fields without consulting a statistician. 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 fill the gaps, if any. Emphasizing simplicity, the fundamental statistical methods are demonstrated by means of arithmetical examples that may be reworked with pencil and paper in a matter of minutes. The results of the rework have to be checked by using SPSS, and in this way professionals are introduced to this psychiatrist-friendly data analysis software. Topics covered include: * An overview of psychiatry research * The organization and collection of data * Descriptive statistics * The basis of statistical inference * Tests of significance * Correlational data analysis * Multivariate data analysis * Meta-analysis * Reporting the results * Statistical software The language of the book is very simple and covers all aspects of statistical methods starting from organization and collection of data to descriptive statistics, statistical inference, multivariate analysis, and meta-analysis. Two chapters on computer applications deal with the most popular data analysis software: SPSS. The book will be very valuable to professionals and post-graduate students in psychiatry and allied fields, such as psychiatric social work, clinical psychology, psychiatric nursing, and mental health education and administration.

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 introduces the latest meta-analytical methods and discusses their applications in the field of psychiatry. A comprehensive list of methods used in meta-analysis has been described in simple language and demonstrated with real-time examples. This informative volume explains the importance of meta-analysis and describes how it differs from narrative and systematic reviews. It also relates the historical development of meta-analysis and explains methods used for locating and selecting the required studies in a given domain. Suitable software is examined in detail as well.

"Prospects for Immortality: A Sensible Search for Life After Death" theorizes how matters concerning the birth of the universe, its ultimate fate, and the creation, evolution, and final destiny of life on earth co-exist with regenerated consciousness. Readers of this volume will be prompted to think about the basic concepts of life, death, and consciousness in a unique way. Written in a style that entertains and informs, author J. Robert Adams speculates on how the transfer of memory and consciousness into the hereafter occurs in conjunction with the physical, chemical, and historical facts already established by science.

This authoritative research guide uses a problem-solving approach to presenting print and electronic resources. Coverage includes: *Definition and deep background sources *Specialized dictionaries, encyclopedias, and handbooks *Current research - Journal Articles and Annual Reviews *Tests and Measures *Bibliographies *U.S. Government Resources *Biographical Resources *Directories and Organizations *Style Guides *Diagnostic Measures *Career Path and Educational Resources *Book Reviews *Major Museums and Archives

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods for PLS-SEM are now readily facilitated by both open-source and commercial software packages. This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications. What makes the book unique is the fact that it thoroughly explains and extensively uses comprehensive Stata (plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM analysis. The book aims to help the reader understand the mechanics behind PLS-SEM as well as performing it for publication purposes. Features: Intuitive and technical explanations of PLS-SEM methods Complete explanations of Stata and R packages Lots of example applications of the methodology Detailed interpretation of software output Reporting of a PLS-SEM study Github repository for supplementary book material The book is primarily aimed at researchers and graduate students from statistics, social science, psychology, and other disciplines. Technical details have been moved from the main body of the text into appendices, but it would be useful if the reader has a solid background in linear regression analysis.

Clearly organised around a single question--is love possible?--Joanne Brown's book provides conceptualizations of love and of its possibility from sociological, philosophical and psychoanalytic viewpoints. Material from biographical, narrative interviews are presented in order to look at how people from two age groups conceptualise love and view its realisation or possibility in their own lives. The book argues for the importance of a psychosocial understanding of love and provides a critical discussion of the philosophy and methods of psychosocial studies.

Concept analysis is an established genre of inquiry in nursing, introduced in the 1970s. Currently, over 100 concept studies are published annually, yet the methods used within this field have rarely been questioned. In Concept Analysis in Nursing: A New Approach, Paley provides a critical analysis of the philosophical assumptions that underpin nursing's concept analysis methods. He argues, provocatively, that there are no such things as concepts, as traditionally conceived. Drawing on Wittgenstein and Construction Grammar, the book first makes a case for dispensing with the traditional concept of a 'concept', and then provides two examples of a new approach, examining the use of 'hope' and 'moral distress'. Casting doubt on the assumption that 'hope' always stands for an 'inner' state of the person, the book shows that the word's function varies with the grammatical construction it appears in. Similarly, it argues that 'moral distress' is not the name of a mental state, but a normative classification used to bolster a narrative concerning nursing's identity. Concept Analysis in Nursing is a fresh and challenging book written by a philosopher interested in nursing. It will appeal to researchers and postgraduate students in the areas of nursing, health, philosophy and linguistics. It will also interest those familiar with the author's previous book, Phenomenology as Qualitative Research.

Research Design for the Behavioral Sciences fills an important gap for the helping professions by offering a blueprint for advanced concepts and an applied approach to understanding quantitative, qualitative, and mixed methods research design. This graduate-level text seamlessly weaves together the philosophy, science, and practical application of the most common methodological frameworks in practice. Advanced research design concepts are presented through clear and in-depth blueprints, applied case studies, myriad examples, and helpful learning activities.Written in detailed yet accessible language, this text describes the foundations of behavioral science research. The authors explore research-based philosophical integration, along with the technical application of every tradition. Through this philosophical and pragmatic approach, students will be able to attain a well-rounded and comprehensive understanding of behavioral science research. This text provides students with the opportunity to reach a greater level of research efficacy though the inclusion of methodological procedures, data analysis methods, reliability/validity standards, ethics, and directions on how to increase the rigor of each approach to research. Instructor resources include an instructor's manual, learning activities, test bank, and PowerPoints. Purchase includes digital access for use on most mobile devices and computers. Key Features: Provides clear, detailed, and contextually accurate examples of writing, quantitative, qualitative, and mixed methods procedures Reviews the paradigmatic hierarchy of each research tradition along with key analytic features in detail Delivers instructions for enhancing the methodological rigor of each approach Analyzes methodology-specific multicultural issues Demonstrates the application of a wide range of research methodologies with case studies Reviews the trends and history in research for counseling, psychology, social work, and marriage and family therapy Offers comprehensive instructor resources including manual, learning activities, test bank, and PowerPoint slides

With over two decades of classroom experience, Michael Passer knows how to guide students through the ins and outs of research methods. In this remarkable text, Passer's experience leads to chapters filled with clear explanations, resonant examples, and contemporary research from across the breadth of modern psychology, all while anticipating common questions and misunderstandings. The new edition has been fully updated to reflect the latest APA style guidelines, as well as the updated APA Code of Conduct and ethical principles. It features full-page infographics summarizing key concepts and fully updated research. It can be packaged FREE with Worth Publishers' LaunchPad Solo for Research Methods-the ideal online component for the text, featuring videos and activities that put students in the role of either experimenter or research subject.

The question of whether someone is psychologically healthy or mentally ill, and the fundamental nature of mental health underlying that question has been debated in cultural, academic, and clinical settings for millennia. This book provides an overview of how people have conceptualized and understood mental illness through the ages. The book begins by looking at mental illness in humanity's evolutionary past then moves through the major historical epochs: the mythological, the Classical, the Middle Ages, the Renaissance, the Enlightenment, and modern, and the postmodern. At each point, it focuses on major elements that emerged regarding how people judged sanity and insanity and places major emphasis on the growing fields of psychiatry and psychology as they emerged and developed. As the book moves into the twenty-first century, Dr. Jenkins presents his integrated model of knowledge, a systemic, holistic model of the psyche that creates a conceptual foundation for understanding both psychological wellness and disorder and approaching assessment and diagnosis. This text provides a valuable exploration of mental health and illness across the ages and gives those already well versed in the subject matter a fresh perspective on the past and new model of knowledge and assessment for the future.

Building off the success of its award-winning first edition, the second edition of Crafting Phenomenological Research continues to be the leading resource for those interested in a concise introduction to phenomenological research in education and social sciences. Joining leading contemporary practitioners, such as van Manen, Giorgi, and Dahlberg, Vagle walks the reader through multiple approaches to designing and implementing phenomenological research, including his post-intentional phenomenology, which incorporates elements of post-structural thinking into traditional methods. Vagle provides readers with methodological tools to build their own phenomenological study, addressing such issues as research design, data gathering and analysis, and writing. Replete with exercises for students, resources for further research, and examples of completed phenomenological studies, this book affords the instructor an easy entree into introducing phenomenology into courses on qualitative research, social theory, or educational research. New to this edition: An additional first chapter that outlines the historical background of phenomenological philosophy and methodology. A feature called "snapshots" that provides brief commentary and/or examples to illustrate concepts and ideas. Updated "resource digs" providing more examples, with the addition of more international resources.

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

This book provides an overview of the innovative, arts-based research method of body mapping and offers a snapshot of the field. The review of body mapping projects by Boydell et al. confirms the potential research and therapeutic benefits associated with body mapping. The book describes a series of body mapping research projects that focus on populations marginalised by disability, mental health status, and other vulnerable identities. Chapters focus on summarising the current state of the art and its application with marginalised groups; analytic strategies for body mapping; highlighting body mapping as a creation and a dissemination process; emerging body mapping techniques including web-based, virtual reality, and wearable technology applications; and measuring the impact of body maps on planning, practice, and behaviour. Contributors and editors include interdisciplinary experts from the fields of psychology, sociology, anthropology, and beyond. Offering innovative ways of engaging in body mapping research, which result in real-world impact, this book is an essential resource for postgraduate students and researchers.

This accessible guide offers a concise introduction to the science behind worry in children, summarising research from across psychology to explore the role of worry in a range of circumstances, from everyday worries to those that can seriously impact children's lives. Wilson draws on theories from clinical, developmental and cognitive psychology to explain how children's worry is influenced by both developmental and systemic factors, examining the processes involved in pathological worry in a range of childhood anxiety disorders. Covering topics including different definitions of worry, the influence of children's development on worry, Generalised Anxiety Disorder (GAD) in children, and the role parents play in children's worry, this book offers a new model of worry in children with important implications for prevention and intervention strategies. Understanding Children's Worry is valuable reading for students in clinical, educational and developmental psychology, and professionals in child mental health.

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning. This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.

Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which both the generalization loss and the marginal likelihood are estimated even if the posterior distribution cannot be approximated by any normal distribution. Features Explains Bayesian inference not subjectively but objectively. Provides a mathematical framework for conventional Bayesian theorems. Introduces and proves new theorems. Cross validation and information criteria of Bayesian statistics are studied from the mathematical point of view. Illustrates applications to several statistical problems, for example, model selection, hyperparameter optimization, and hypothesis tests. This book provides basic introductions for students, researchers, and users of Bayesian statistics, as well as applied mathematicians. Author Sumio Watanabe is a professor of Department of Mathematical and Computing Science at Tokyo Institute of Technology. He studies the relationship between algebraic geometry and mathematical statistics.

A New Way of Analyzing Object Data from a Nonparametric Viewpoint Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds. It also presents in-depth applications to practical problems arising in a variety of fields, including statistics, medical imaging, computer vision, pattern recognition, and bioinformatics. The book begins with a survey of illustrative examples of object data before moving to a review of concepts from mathematical statistics, differential geometry, and topology. The authors next describe theory and methods for working on various manifolds, giving a historical perspective of concepts from mathematics and statistics. They then present problems from a wide variety of areas, including diffusion tensor imaging, similarity shape analysis, directional data analysis, and projective shape analysis for machine vision. The book concludes with a discussion of current related research and graduate-level teaching topics as well as considerations related to computational statistics. Researchers in diverse fields must combine statistical methodology with concepts from projective geometry, differential geometry, and topology to analyze data objects arising from non-Euclidean object spaces. An expert-driven guide to this approach, this book covers the general nonparametric theory for analyzing data on manifolds, methods for working with specific spaces, and extensive applications to practical research problems. These problems show how object data analysis opens a formidable door to the realm of big data analysis.

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Reciprocity Rules explores the rich and complicated relationships that develop between anthropologists and research participants over time. Focusing on compensation and the creation of friendship and "family" relationships, contributors discuss what, when, and how researchers and the people with whom they work give to each other in and beyond fieldwork. Through reflexivity and narrative, the contributors to this edited collection, who are in various stages in their professional careers and whose research spans three continents and eight countries, reflect on the ways in which they have compensated their research participants and given back to host communities, as well as the varied responses to their efforts. The contributors consider both material and non-material forms of reciprocity, stories of successes and failures, and the taken-for-granted notions of compensation, friendship, and "helping." In so doing, they address the interpersonal dynamics of power and agency in the field, examine cultural misunderstandings, and highlight the challenges that anthropologists face as they strive to maintain good relations with their hosts even when separated by time and space. The contributors argue that while learning, following, openly discussing, and writing about the local rules of reciprocity are always challenging, they are essential to responsible research practice and ongoing efforts to decolonize anthropology.