Software is cut and dried - every button you press has a predictable effect - but qualitative analysis is open ended and unfolds in unpredictable ways. This contradiction is best resolved by separating analytic strategies - what you plan to do - from software tactics - how you plan to do it. Expert NVivo users have unconsciously learned to do this. The Five-Level QDA (R) method unpacks the process so that you can learn it consciously and efficiently. The first part of the book explains how the contradiction between analytic strategies and software tactics is reconciled by "translating" between them. The second part provides both an in-depth description of how NVivo works and comprehensive instruction in the five steps of "translation". These steps are illustrated with examples from a variety of research projects. The third part contains real-world qualitative research projects from a variety of disciplines, methodologies, and kinds of qualitative analysis, all illustrated in NVivo using the Five-Level QDA method. The book is accompanied by three sets of video demonstrations on the companion website. The book and accompanying videos illustrate the Windows version of NVivo. As there are some differences in screen and interface design between the Mac and Windows versions please watch the video 'The NVivo Mac Interface' in the Component Orientation series of videos (available on the companion website). The Five-Level QDA method is based on the authors' combined 40 years of experience teaching NVivo and other software packages used as platforms for conducting qualitative analysis. After many years observing their students' challenges they developed the Five-Level QDA method to describe the process that long-time NVivo experts unconsciously adopt. The Five-Level QDA method is independent of software program or methodology, and the principles apply to any type of qualitative project. Please see the following URL to access the accompanying materials for this book: https://www.qdaservices.co.uk/five-level-qda

For disciplines concerned with human well-being, such as medicine, psychology, and law, statistics must be used in accordance with standards for ethical practice. A Statistical Guide for the Ethically Perplexed illustrates the proper use of probabilistic and statistical reasoning in the behavioral, social, and biomedical sciences. Designed to be consulted when learning formal statistical techniques, the text describes common instances of both correct and false statistical and probabilistic reasoning. Lauded for their contributions to statistics, psychology, and psychometrics, the authors make statistical methods relevant to readers day-to-day lives by including real historical situations that demonstrate the role of statistics in reasoning and decision making. The historical vignettes encompass the English case of Sally Clark, breast cancer screening, risk and gambling, the Federal Rules of Evidence, "high-stakes" testing, regulatory issues in medicine, difficulties with observational studies, ethics in human experiments, health statistics, and much more. In addition to these topics, seven U.S. Supreme Court decisions reflect the influence of statistical and psychometric reasoning and interpretation/misinterpretation. Exploring the intersection of ethics and statistics, this comprehensive guide assists readers in becoming critical and ethical consumers and producers of statistical reasoning and analyses. It will help them reason correctly and use statistics in an ethical manner.

Originally published in 1976, the authors of six of the most widely quoted works in behavioural science related to education, at the time, here describe in detail their research work, including its origins, planning and implementation. The accounts are unusual, not only for their technical detail but for their candour. The brief was to put the heart and brains back into accounts of research so the authors comment not only on the research design, but on the personal and professional problems they had to overcome. They also reflect on the reception of their work, and the way in which it has been adapted, misunderstood or deliberately distorted to support arguments of widely differing ideological pressure groups. The book shows how ingenuity and persistence as well as technical competence lie at the heart of the research process. The authors do not give the normal depersonalised, streamlined account which gives a false, mechanical picture of research as an occupation, but show it to be a profound personal and professional experience as they comment on the thought that lay behind their work and the way it was finally produced for publication. Dr Shipman has written a short introduction to each chapter, and contributed a concluding chapter relating the six research experiences to conventional views on the research process and to the part played by research evidence in policy making.

This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum's Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV is new to this edition; it discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher's striking advice for observational studies: "make your theories elaborate." This new edition features updated exploration of causal influence, with four new chapters, a new R package DOS2 designed as a companion for the book, and discussion of several of the latest matching packages for R. In particular, DOS2 allows readers to reproduce many analyses from Design of Observational Studies.

Statistical methodology is often conceived by social scientists in a technical manner; they use it for support rather than for illumination. This two-volume set attempts to provide some partial remedy to the problems that have led to this state of affairs. Both traditional issues, such as analysis of variance and the general linear model, as well as more novel methods like exploratory data analysis, are included. The editors aim to provide an updated survey on different aspects of empirical research and data analysis, facilitate the understanding of the internal logic underlying different methods, and provide novel and broader perspectives beyond what is usually covered in traditional curricula.

This comprehensive reference organizes extensive definitions and examples of key concepts in quantitative research into a single, convenient source. Alphabetically arranged and cross-referenced, The Handbook of Research and Quantitative Methods In Psychology presents: experimental procedures, research designs, statistical methods, information theory, psychophysics, behavioral terminology, scaling and testing.

Drawing on the authors varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.

Making sense of such bewildering problems as hallucinations, paranoia, depression, and anxiety seems an incredible challenge, but modern psychiatry is able to bring understanding and change to many of those whose lives are impaired by psychiatric problems. This is not accomplished through the application of one dominant psychological theory, but through the integration of perspectives of many such theories in this diverse field into a befitting approach-the biopsychosocial model. Application of the biopsychosocial model will allow for understanding the patient in biological, psychological, and social terms simultaneously, and provide a holistic picture with multiple strategies for treatment. In this book, the author takes a step back from the assessment to demonstrate to the student methods of the information gathered from the patient into a clinically useful whole, essentially showing exactly how and why the psychiatrist arrives at an intervention.

Presenting the proceedings of a conference held at Syracuse University in honor of S.S. Stevens, a pioneer in the scaling of sensory magnitudes and the originator of the method of magnitude estimation, this volume brings together the work of 20 authorities on the procedures of ratio scaling. These experts--psychophysicists, physiologists, and theoreticians--offer their views on whether or not psychological magnitudes can be measured and whether the judgments of psychological magnitudes constitute the basis for the construction of a ratio scale. Also discussed is the question of whether any single method could stand out as a potential standard technique for measuring psychological magnitudes.

This book declines to take for granted the widespread assumption that existing psychometric procedures provide scientific measurement. The currently fashionable concepts of measurement within psychology -- operationalism and representationalism -- are critically examined, and the classical view, that measurement is the assessment of quantity, is defended. Within this framework, it is shown how conjoint measurement can be used to test the hypothesis that variables are quantitative. This theme is developed in detail using familiar psychological examples, such as Thurstone's law of comparative judgment, multidimensional scaling, and Coombs' theory of unfolding.

Based on a tremendous increase in the development of psychometric theories in the past decade -- ranging from techniques for criterion-referenced testing to behavioral assessment, generalizability, and item response theory -- this book offers a summary of core issues. In so doing, it provides a comprehensive survey of reliability, validity, and item analysis from the perspectives of classical true-score model, generalizability theory, item response theory, criterion-referenced testing, and behavioral assessment. Related theoretical issues such as item bias, equating, and cut-score determination are also discussed. This is an excellent text for courses in statistics, research methods, behavioral medicine and cognitive science as well as educational, school, experimental, counseling/social, clinical, developmental, and personality psychology.

Sponsored by the American Psychological Association, this is a representation of the proceedings of the National Conference on Graduate Education in Psychology. The proceedings begin with general introductory material, after which ten major issues are presented and discussed, answering such questions as: How can science and practice be combined? Should there be a core or individualized curriculum? What are the implications of the institutional and organizational setting? Are programs responsible for the marketability of their graduates? Major themes cutting across many presentations and recommendations include: the perceived unity or disunity of psychology as it is taught and as it organizationally exists; the acceptance and encouragement of diversity within a unified discipline; the quality of graduate education and its students; and recognition that graduate education involves people as well as curricula. Since the issues covered are of great concern to scientists, health service providers and educators alike, this book should have a significant impact on the field.

George and Louise Spindler are widely regarded as significant founders of the field of educational anthropology. This book brings together their best, most seminal work from the last 50 years--a time frame representing the developmental epoch of the field--and binds them together with a master commentary by George Spindler. Previously scattered over a wide range of publications, the articles collected here allow for a unified view of the Spindlers' work and of the development of the field. The book opens with an insightful Foreword by Henry T. Trueba, a fascinating piece titled "A Life With Anthropology and Education: Interviews With George and Louise Spindler by Ray McDermott and Frederick Erickson," and George Spindler's "Previews" essay which gives the reader a grasp of the whole to which the parts of the book contribute. These pieces frame and contextualize the work that follows. In Part I, Character Defining, many of the major themes of this volume are first encountered; this section sets the stage for what follows. Part II, Comparisons, focuses on comparison, which the Spindlers view as essential to an anthropological approach. Part III, Ethnography in Action, is devoted to the explicit exposition of ethnographic methods (though actually every piece in the book is a demonstration of method). Part IV, American Culture, moves from a traditional representation of American Culture to a processual analysis of how the culture is transmitted in real situations, and finally to an interpretation of right-wing actions that seem to constitute a reactive movement; the implications for education are pursued. Part V, Cultural Therapy , explains what cultural therapy is and how it may be applied to teachers and students. The volume concludes with Part VI, Orientation, Susan Parman's overview of the works of the Spindlers that spans their whole career.

This book sheds new light on the life and the influence of one of the most significant critical thinkers in psychology of the last century, Theodore R. Sarbin (1911-2005). In the first section authors provide a comprehensive account of Sarbin's life and career. The second section consists in a collection of ten publications from the last two decades of his career. The essays cover topics such as the adoption of contextualism as the appropriate world view for psychology, the establishment of narrative psychology as a major mode of inquiry, and the rejection both mechanism and mentalism as suitable approaches for psychology. The book is historically informed and yet focused on the future of psychological theory and practice. It will engage researches and scholars in psychology, social scientists and philosophers, as well general readership interested in exploring Sarbin's theories.

The systematic scientific investigation of human perception began over 130 years ago, yet relatively little is known about how we identify complex patterns. A major reason for this is that historically, most perceptual research focused on the more basic processes involved in the detection and discrimination of simple stimuli. This work progressed in a connectionist fashion, attempting to clarify fundamental mechanisms in depth before addressing the more complex problems of pattern recognition and classification. This extensive and impressive research effort built a firm basis from which to speculate about these issues. What seemed lacking, however, was an overall characterization of the recognition problem - a broad theoretical structure to direct future research in this area. Consequently, our primary objective in this volume, originally published in 1981, was not only to review existing contributions to our understanding of classification and recognition, but to project fruitful areas and directions for future research as well. The book covers four areas: complex visual patterns; complex auditory patterns; multi-dimensional perceptual spaces; theoretical pattern recognition.

Straightforward and concise, the second edition of A Guide to Writing for Human Service Professionals offers students and professionals practical tools to improve their writing. In his animated and highly accessible teaching voice, Glicken presents the rules of punctuation, grammar, and APA style in jargon-free language that's easy to understand. Chapters include detailed, real-world examples on how to write academic papers, client assessments and evaluations, business letters, research proposals and reports, papers for mass audiences, requests for funding, and much more. Glicken provides the most comprehensive writing guide available in an engaging and digestible format, including end-of-chapter exercises that allow readers to further practice their writing and critical thinking skills. A Guide to Writing for Human Service Professionals is an invaluable resource for current and future human service professionals across social work, psychology, and counseling. Updates to the Second Edition include: *New writing exercises in every chapter to help current and future human service professionals improve critical thinking and expository writing skills *New discussion on social media writing, cyberslang, and writing articles for the mass media on issues related to the human services *A greater emphasis on the difference between politically correct writing and writing that shows sensitivity to diversity *Expanded coverage of critical thinking and writing, conducting research, and plagiarism *New examples of resume writing, business letters, and reference letters *Expanded discussion of the importance of writing clear mission statements and agency goals

This book brings together psychometric, cognitive science, policy, and content domain perspectives on new approaches to educational assessment -- in particular, constructed response, performance testing, and portfolio assessment. These new assessment approaches -- a full range of alternatives to traditional multiple-choice tests -- are useful in all types of large-scale testing programs, including educational admissions, school accountability, and placement. This book's multi-disciplinary perspective identifies the potential advantages and pitfalls of these new assessment forms, as well as the critical research questions that must be addressed if these assessment methods are to benefit education.

Do you want to spend less time studying but end up with better grades, and a deeper understanding of the subject? Studying psychology is a skill that can be learned. In this unique and practical 'how to' guide, Warren Davies offers some simple techniques that will enable students to retain information, organise their workload, and be more productive. By applying some simple and easy-to-make changes to your study habits, you will learn how to: Get more work done in less time Use memory techniques to help you breeze through exams Beat procrastination Develop a deep grasp of difficult topics Write excellent essays (including how to avoid the seven most common essay errors) Cut your study time in half Understand the 'results' section of research papers Write a dissertation to publishable standard. This book is written specifically with psychology undergraduate students in mind, and as such will enhance your learning and improve your grades with techniques that actually work.

This book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation. It discusses the pros and cons of various techniques and concepts, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically relevant developments in the field, and demonstrates the use of recent multiple imputation techniques designed for situations where distributional assumptions of the classical multiple imputation solutions are violated. In addition, the book features numerous practical tutorials for widely used R software packages to generate multiple imputations (norm, pan and mice). The provided R code and data sets allow readers to reproduce all the examples and enhance their understanding of the procedures. This book is intended for social and health scientists and other quantitative researchers who analyze incompletely observed data sets, as well as master's and PhD students with a sound basic knowledge of statistics.

Primary research in education and social sciences is marked by a diversity of methods and perspectives. How can we accommodate and reflect such diversity at the level of synthesizing research? What are the critical methodological decisions in the process of a research synthesis, and how do these decisions open up certain possibilities, while closing down others? This book draws upon methodologically diverse literature on research synthesis methods and primary research methods to develop a framework for synthesizing research. It presents a Methodologically Inclusive Research Synthesis framework to facilitate critical and informed decision-making among the producers and users of research synthesis. Three guiding principles for a quality research synthesis are proposed: informed subjectivity and reflexivity, purposefully informed selective inclusivity, and audience-appropriate transparency. The book then provides a thorough discussion of how these principles might be enacted in the following six phases: -identifying an appropriate epistemological orientation -identifying an appropriate purpose -searching for relevant literature -evaluating, interpreting and distilling evidence from selected studies -constructing connected understandings -communicating with an audience. A wide range of techniques and perspectives from postpositivist, interpretive, participatory, critical and postmodern traditions are considered in the book, and Suri opens up new areas of debate by exploring numerous aspects of research syntheses from a methodologically inclusive perspective. The book will be valuable reading for researchers and postgraduates in education and social sciences.

This unusual book was written to provide a glimpse into the inner "Rorschach" world of individuals -- psychology students in training -- representing the basic Rorschach subtypes. The Rorschach records of these graduate students in clinical psychology are presented along with their own interpretations and analyses of their records. In short, The Inside Story offers both a new approach to learning projective diagnostic methods such as the Rorschach and a new experience in the adventure of self-understanding.

First Published in 1987. Routledge is an imprint of Taylor & Francis, an informa company.

This classic volume outlines, for both students and professionals, the mathematical theories and equations that are necessary for evaluating a test and for quantifying its characteristics. The author utilizes formulas that evaluate both the reliability and the validity of tests. He also provides the means for evaluating the reliability and validity of total test scores and individual item analysis. The work remains one of the only books on classical test theory to discuss applications, "true score" theory, the effect of test length on reliability and validity, and the effects of univariate and multivariate selection on validity.

This outstanding presentation of the fundamentals of multidimensional scaling illustrates the applicability of MDS to a wide variety of disciplines. The first two sections provide ground work in the history and theory of MDS. The final section applies MDS techniques to such diverse fields as physics, marketing, and political science.

"This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some time. The discussion of mixtures with heavy tails and asymmetric distributions will place this text as the authoritative, modern reference in the mixture modeling literature." (Douglas Steinley, University of Missouri) Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for established researchers and newcomers to the field. A history of mixture models as a tool for classification is provided and Gaussian mixtures are considered extensively, including mixtures of factor analyzers and other approaches for high-dimensional data. Non-Gaussian mixtures are considered, from mixtures with components that parameterize skewness and/or concentration, right up to mixtures of multiple scaled distributions. Several other important topics are considered, including mixture approaches for clustering and classification of longitudinal data as well as discussion about how to define a cluster Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.