Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

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.

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas.

Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women's issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials. Featuring contributions from leadership experts and statisticians at various career stages, this unique and insightful text: Examines leadership within the roles of statistician and data scientist from international and diverse perspectives Supplies a greater understanding of leadership within teams, research consulting, and project management Encourages reflection on leadership behaviors, promoting both natural and organizational leadership Identifies existing opportunities to foster creative outputs and develop strong leadership voices Includes real-life stories about overcoming barriers to leadership Leadership and Women in Statistics explains how to convert a passion for statistical science into visionary, ethical, and transformational leadership. Although the context focuses on statistics, the material applies to almost all fields of endeavor. This book is a valuable resource for those ready to consider leadership as an important element of their careers, and for those who are already leaders but want to deepen their perspectives on leadership. It makes an ideal text for group leadership training as well as for individual professional development.

A Sound Basis for the Theory of Statistical Inference Measuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct. The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.

In 1968, Stanley Kubrick completed and released his magnum opus motion picture 2001: A Space Odyssey; a time that was also tremendously important in the formation of the psychoanalytic theory of Jacques Lacan. Bringing these figures together, Bristow offers a study that goes beyond, as the film did. He extends Lacan's late topological insights, delves into conceptualisations of desire, in G. W. F. Hegel, Alexandre Kojeve, and Lacan himself, and deals with the major themes of cuts (filmic and psychoanalytic); space; silence; surreality; and 'das Ding', in relation to the movie's enigmatic monolith. This book is a tour de force of psychoanalytic theory and space odyssey that will appeal to academics and practitioners of psychoanalysis and film studies, as well as to any fan of Kubrick's work.

In this book the author's theoretical framework builds on linguistic and psychological research, arguing that similar image-schematic notions should be grouped together into interconnected family hierarchies, with complexity increasing with regard to the addition of spatial and conceptual primitives. She introduces an image schema logic as a language to model image schemas, and she shows how the semantic content of image schemas can be used to improve computational concept invention. The book will be of value to researchers in artificial intelligence, cognitive science, psychology, and creativity.

Cases and Stories of Transformative Action Research builds on its companion book, Principles and Methods of Transformative Action Research, by describing and analyzing dozens of examples of successful action research efforts pursued in the past five decades by students and faculty of the Western Institute for Social Research. Some projects are large-scale, and some are modest interventions in the everyday lives of those participating. Some are formal organizational efforts; others are the results of individual or small group initiatives. Included are chapters on community needs assessments and innovative grassroots approaches to program evaluation; the challenges of improving our decision-making during the crisis of the COVID-19 pandemic; strategies of intellectual activism in addressing the growing problem of workplace bullying; action research to preserve and share the history of the Omaha tribe; and plans for an innovative school-based project based on collaborative action-and-inquiry between students and Artificial Intelligence. In addition, there are a number of detailed stories about the use of transformative action research in such areas as somatic and trauma counseling, ethnic studies, health disparities, gender differences, grassroots popular education, and the improvement of statewide steps for preventing child abuse, among many others. This book can serve as an undergraduate or graduate social sciences text on research methods. It is also a guidebook for action-oriented research by academics, professionals, and lay people alike.

This book offers different theoretical approaches about what clinical research is. Clinical Research in Psychoanalysis is a unique contribution to the attempts to bridge the gap between clinicians and researchers and to create a culture of a more rigorous and systematic inquiry. It provides an innovative experience because for the first time different methods and perspectives were used to analyse one same clinical material. This was done by analysts from different working parties of the International Psychoanalytical Association (IPA), from a range of different schools of psychoanalytic thought. This allows the reader to have a vision of the different methods that are currently being used by some working parties of the IPA and to learn about the strengths of each one for certain situations and types of research. This book revaluates clinical research, intending to make links between the analysts working through the working parties and the different ways of thinking in clinical research. By covering key topics, such as how working parties can facilitate different types of research; the place of metaphor in psychoanalytic research and practice; and the future for psychoanalytic research, this text is a fruitful dialogue between different theoretical conceptions and between clinicians and researchers, that will expand our perspectives on the evidence we find in clinical material and will broaden our views on the patient. This book offers a unique and invaluable experience to psychologists and psychoanalysts who are trying to improve their clinical practice and bring research evidence into their psychoanalytic practice. It is an invaluable contribution to psychoanalytic training of candidates, teachers, and students.

This book explores the ways in which the spatio-temporal contingency of human life is being conceived in different fields of research. Specifically, it looks at the relationship between the situatedness of human life, the situation or place in which human life is supposed to be situated, and the dimensions of space and time in which both situation and place are usually themselves supposed to be situated. Over the last two or three decades, the spatio-temporal contingency of human life has become an important topic of research in a broad range of different disciplines including the social sciences, the cultural sciences, the cognitive sciences, and philosophy. However, this research topic is referred to in quite different ways: while some researchers refer to it in terms of "situation", emphasizing the "situatedness" of human experience and action, others refer to it in terms of "place", emphasizing the "power of place" and advocating a "topological" or "topographical turn" in the context of a larger "spatial turn". Interdisciplinary exchange is so far hampered by the fact that the notions referred to and the relationships between them are usually not sufficiently questioned. This book addresses these issues by bringing together contributions on the spatio-temporal contingency of human life from different fields of 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

"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.

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.

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.

Originally published in 1969, Behavioral Problems in Geography unpacks and identifies elements of behavioral models and theories. The book seeks to examine their specific effects on spatial activity and to operationalize some of the concepts previously used in a subjective and descriptive manner. All papers, are united by a common concern for the building of geographic theory regarding human behavior. Contributions in the volume vary a great deal in their emphasis ranging from philosophy and review, to theorizing and operationalization. Each paper recognizes the importance of examining the behavioural basis of spatial activity. This book will appeal to scholars of geography and psychology alike.

Featuring a practical approach with numerous examples, the second edition of Categorical Data Analysis for the Behavioral and Social Sciences focuses on helping the reader develop a conceptual understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analysis methods and emphasize specific research questions that can be addressed by each analytic procedure, including how to obtain results using SPSS, SAS, and R, so that readers are able to address the research questions they wish to answer. Each chapter begins with a "Look Ahead" section to highlight key content. This is followed by an in-depth focus and explanation of the relationship between the initial research question, the use of software to perform the analyses, and how to interpret the output substantively. Included at the end of each chapter are a range of software examples and questions to test knowledge. New to the second edition: The addition of R syntax for all analyses and an update of SPSS and SAS syntax. The addition of a new chapter on GLMMs. Clarification of concepts and ideas that graduate students found confusing, including revised problems at the end of the chapters. Written for those without an extensive mathematical background, this book is ideal for a graduate course in categorical data analysis taught in departments of psychology, educational psychology, human development and family studies, sociology, public health, and business. Researchers in these disciplines interested in applying these procedures will also appreciate this book's accessible approach.

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.

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.

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.

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.

Longitudinal research is an essential element in the investigation of human development over time, with considerable advantages over more widely used cross-sectional research designs. This book examines the scope for longitudinal studies in a range of developmental fields, emphasizing the advantages of this approach for the investigation of causal mechanisms and processes and the dynamics of development over the life-span. It also discusses methodological issues and some of the practical and ethical problems that longitudinal research may present. Drawing on the final conference in the European Science Foundation's network dealing with longitudinal research on individual development, this is a valuable reference work for behavioural and developmental scientists. The distinguished contributors review normal and disordered development in the emotional, cognitive and social domains, including valuable discussions of gene-environment interactions, the maturation of the human brain, and issues relating to aging. As a source of information and ideas this volume, the concluding work in this series, will be of interest to practitioners and research workers in developmental disciplines at any stage of the life-cycle.

In this edited book, expert assessors illustrate through case examples how they apply psychoanalytic theory to different clinical settings. These settings include private practice, neuropsychological, medical, forensic, personnel, custody, school, and psychiatric-residential. Psychoanalytic Assessment Applications for Different Settings allows the reader to track the assessor's work from start to finish. Each chapter presents a description of the clinical setting in which the assessment occurred; a detailed review of the referral and patient history; test selection and test findings with supporting data drawn from self-report, and cognitive and personality performance-based measures; psychiatric and psychodynamic diagnoses; implications and recommendations; discussion of the feedback process; and assessor-self reflections on the case. Throughout the book, psychodynamic concepts are used to help understand the test data. The authors are experts in the psychodynamic assessment of clients in private practice, educational, medical, neuropsychological, and forensic settings. The findings are derived from methods particular to each setting, with supporting data highlighted and woven throughout the interpretive process. Students, educators, practitioners, and the professionals who collaborate with assessors will benefit from this book's offerings.

In this edited book, expert assessors illustrate through case examples how they apply psychoanalytic theory to different clinical settings. These settings include private practice, neuropsychological, medical, forensic, personnel, custody, school, and psychiatric-residential. Psychoanalytic Assessment Applications for Different Settings allows the reader to track the assessor's work from start to finish. Each chapter presents a description of the clinical setting in which the assessment occurred; a detailed review of the referral and patient history; test selection and test findings with supporting data drawn from self-report, and cognitive and personality performance-based measures; psychiatric and psychodynamic diagnoses; implications and recommendations; discussion of the feedback process; and assessor-self reflections on the case. Throughout the book, psychodynamic concepts are used to help understand the test data. The authors are experts in the psychodynamic assessment of clients in private practice, educational, medical, neuropsychological, and forensic settings. The findings are derived from methods particular to each setting, with supporting data highlighted and woven throughout the interpretive process. Students, educators, practitioners, and the professionals who collaborate with assessors will benefit from this book's offerings.

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.