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

Participation is a vital element of working with children and young people ensuring that services are meeting their needs as well as promoting citizenship, resilience and general well-being. The Evaluator s Cookbook contains 21 participatory evaluation exercises for use with children, young people and families/community groups. Attractively and clearly presented, the exercises are very easy to use and come with suggestions for use and instructions on how to create the equipment needed. They will appeal to a wide range of people and can be used in a variety of informal and formal settings and most of the exercises are suitable for use with disabled children or children with special needs, as well as people with English as a second language. The book also explores why, how and where participatory research and evaluation should take place and provides suggestions on how the findings can be presented in imaginative ways. This unique book is an invaluable resource for those wishing to consult with children and families or evaluate social, health and education services in diverse cultural settings.

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 MAXQDA 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 MAXQDA 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 MAXQDA using the Five-Level QDA method. The book is accompanied by three sets of video demonstrations on the Companion Website. The functionality and interface design of MAXQDA for Windows and Mac are identical. The Five-Level QDA method learned from this book is therefore the same whether you are working on a Mac or Windows computer. The Five-Level QDA method is based on the authors' combined 40 years of experience teaching MAXQDA 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 MAXQDA 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

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 ATLAS.ti 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 ATLAS.ti 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 ATLAS.ti using the Five-Level QDA method. The book is accompanied by three sets of videos demonstrations on the Companion Website. While this book uses screenshots from the current ATLAS.ti Version 8, it is still fully applicable to users of older versions. The book and accompanying videos illustrate the Windows version of ATLAS.ti. As there are some differences in screen and interface design between the Mac and Windows versions please watch the video 'The ATLAS.ti Mac Interface' in the Component Orientation series of videos (available September 2017) The Five-Level QDA method is based on the authors' combined 40 years of experience teaching ATLAS.ti 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 ATLAS.ti 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

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book's CRC Press web page. Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab, R, SAS, SPSS, and Stata.

This text focuses on the experimental methods and the associated terminology encountered in the research literature of psychology. Initially, the content is kept simple, so as not to distract from the information on research technique and philosophy. Interesting psychological questions from well researched areas are then examined in detail, permitting a fuller discussion of the problems encountered in specific paradigms. It is in this fashion that the book offers both methods and content.
Unique features of this text include:
* a detailed discussion of the process of theorizing, coupled with a close examination of psychological constructs, offers the reader an opportunity to see how psychologists think about, develop, and modify their theories, and the part played by research in changing explanations of behavior.
* Although it is common for psychologists to be self-conscious in their reasoning, it is uncommon to see an analysis of the logic that they use to draw conclusions. Presenting material that is rarely verbalized but readily acknowledged by experienced researchers, the text contains an overt analysis of the logic of drawing conclusions from research.
* Instructors are given a choice among 15 chapters to focus on or combine to suit the course's concentration. For example, instructors have the option of focusing on experimental psychology or a broad-based course including material on research methods in experimental, social, clinical, and applied psychology.
* Courses in experimental psychology or research methods are required for every psychology major. Statistical understanding is vital for this curriculum, and this text contains a comprehensive chapter on statistics making it ideal for courses that combine statistics and experimental methods.
Other important coverage includes:
* an all-inclusive summary of the material found in an introductory statistics class. Although courses in research methods and experimental psychology usually have a statistics prerequisite, the students rarely remember the material when entering the research course. This text provides the instructor with the option of simply assigning the statistics information as a review, rather than repeating the lectures. If the course requirements are such as to necessitate a joint statistics and research methods course -- with the instructor lecturing on both topics -- this text could serve as the single text for the course. A helpful discussion -- accompanied by a valuable table -- demonstrates how to choose an appropriate statistic. All necessary formulas and other familiar statistical procedures -- illustrating computational steps -- are also featured.
* a detailed discussion of how to develop tests for use in research. Aside from the value of this information for any researcher, it can be particularly helpful to students who are required to develop original experiments.
* an elaborate discussion of methodological issues in outcome research, using smoking cessation and weight reduction programs as examples.
Test bank disks for "Experimental Methods in Psychology, " -- free to adopters -- consist of an average of six short-answer, 11 fill-in-the-blank, and 11 multiple-choice questions for each chapter. The files are in both ASCII and Word-for-Windows formats.

This new edition of one of the most widely read textbooks in its field introduces the reader to data analysis with the most powerful and versatile statistical package on the market: IBM SPSS Statistics 19. Each new release of SPSS Statistics features new options and other improvements. There remains a core of fundamental operating principles and techniques which have continued to apply to all releases issued in recent years and have been proved to be worth communicating in a small volume. This practical and informal book combines simplicity and clarity of presentation with a comprehensive treatment of the use of IBM SPSS Statistics 19 for the description, exploration and confirmation of data. As in earlier editions, coverage has been extended to address the issues raised by readers since the previous edition. In this edition, there is an introduction to the Analysis of Covariance (ANCOVA). Each statistical technique is presented in a realistic research context and is fully illustrated with annotated screen shots of SPSS dialog boxes and output. The first chapter sets the scene with a survey of typical research situations, key terms and clear signposts to the location of each technique in the book. It also offers guidance on the choice of statistical techniques, and advice (based on the American Psychological Association's guidelines) on how to report the results of a statistical analysis. The next chapters introduce the reader to the use of SPSS, beginning with the entry, description and exploration of data. There is also a full description of the capabilities of the versatile Chart Builder. Each of the remaining chapters concentrates on one particular kind of research situation and the statistical techniques that are appropriate. In summary, IBM SPSS Statistics 19 Made Simple Gets you started with SPSS. Shows you how to describe and explore a data set with the help of SPSS's extensive

This text takes the guesswork out of using SPSS, with screenshots that show each step for calculating each statistic. It includes extensive coverage of how to format raw SPSS output for inclusion in research reports. End-of-chapter exercises help students master their newly acquired skills. An instructor's answer key will be included with each complimentary examination copy. New to this edition: This edition includes an abundance of instructional screenshots, all of which have been updated to reflect the new look of IBM SPSS Statistics Version 23. Instructor ancillaries that accompany this text include PowerPoints for classroom instruction, and test banks in text format and importable to Respondus.

This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts, using Mplus as the software tool, and demonstrating the various functions available for these analyses in Mplus, which is widely used by researchers in various fields, including most of the social sciences. In particular, Mplus offers users a wide array of tools for latent variable modelling, including for multilevel data.

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.

Computer simulation has become an important means for obtaining knowledge about nature. The practice of scientific simulation and the frequent use of uncertain simulation results in public policy raise a wide range of philosophical questions. Most prominently highlighted is the field of anthropogenic climate change are humans currently changing the climate? Referring to empirical results from science studies and political science, Simulating Nature: A Philosophical Study of Computer-Simulation Uncertainties and Their Role in Climate Science and Policy Advice, Second Edition addresses questions about the types of uncertainty associated with scientific simulation and about how these uncertainties can be communicated. The author, who participated in the United Nations Intergovernmental Panel on Climate Change (IPCC) plenaries in 2001 and 2007, discusses the assessment reports and workings of the IPCC. This second edition reflects the latest developments in climate change policy, including a thorough update and rewriting of sections that refer to the IPCC.

This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound. Particular emphasis is placed on the common foundation of many models used in practice. In addition, the book focuses on the formulation of appropriate statistical models to study problems in business, economics, and the social sciences, as well as on how to interpret the results from statistical analyses. The book will be useful to students who are interested in rigorous applications of statistics to problems in business, economics and the social sciences, as well as students who have studied statistics in the past, but need a more solid grounding in statistical techniques to further their careers. Jacco Thijssen is professor of finance at the University of York, UK. He holds a PhD in mathematical economics from Tilburg University, Netherlands. His main research interests are in applications of optimal stopping theory, stochastic calculus, and game theory to problems in economics and finance. Professor Thijssen has earned several awards for his statistics teaching.

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.

This book presents the reader with a set of diverse, carefully developed and clearly specified systems of transcription and coding, arising from contrasting theoretical perspectives, and presented as alternative choices, situated within the theoretical domain most natural to each. The perspectives represented include first and second language acquisition, interethnic and crosscultural interaction, information structure, and the study of discourse influences on linguistic expression. In the contributed chapters, the designers of these systems provide a distillation of collective experiences from the past quarter century, telling in their own words their perspectives on language processes, how these perspectives have shaped their choice of methodology in transcription and coding of natural language, and describing their systems in detail. Overview chapters by the editors then provide design principles and guidelines concerning issues pertinent to all systems, including such things as reliability, validity, ease of learning, computational tractability, and robustness against error. The final chapter is a compendium of existing computerized archives of language data and information sources together with details concerning data access and use.

In Real Data, students predict the answers to interesting questions. Then they analyze data supplied by leading researchers to see if there is empirical support for their predictions. Students get practice in computing all the major statistics usually covered in an introductory statistics course. Because each of the 35 exercises in Part A deals with only a limited number of statistics, the workbook is easily coordinated with all introductory statistics textbooks. Part A emphasizes small data sets that are useful whether students are using calculators or computers. The exercises in this part are highly structured so students know exactly what is required of them. Part B provides larger data sets for comprehensive analysis by computer users. Loosely structured, the data sets allow you to specify which statistics should be computed. Sample topics: Kissing and Sexual Harassment; Basic Trust of Rape Survivors; Gambling and Stealing; Pregnancy Risk Among Adolescents Who Had Been Sexually Abused; Boys Interacting with Their Fathers; Racial Differences in Seeking Medical Assistance; Instructors Clothing and Student Evaluations; Students Attitudes Toward Math; and Physician-Assisted Suicide. Using real data for analysis makes the traditional statistics class come alive.

These two companion volumes provide a comprehensive review and critical evaluation of the major DSM-III and DSM-III-R child disorders. Their major goal is to provide diagnostic and assessment guidelines that are based on scientific literature in specific clinical domains. Each chapter contains a discussion of the historical background of a particular diagnosis, definitional issues, a critical but selective review of the literature addressing the diagnosis in question, proposed changes in the diagnostic criteria based on the available literature, and proposed assessment models and methods based on the designated criteria. Given the scientific bases for many of these discussions of diagnostic criteria, these two volumes will serve professionals and graduate students in a wide variety of fields: clinical child psychology, child psychiatry, pediatrics, pediatric and school psychology, special education, social work, and other child mental health specialties.

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.

Methodological Problems with the Academic Sources of Popular Psychology: Context, Inference, and Measurement examines the relationship between academic and popular psychology from a critical perspective with a focus on issues of methodology. The monograph traces the path from ideas in reputable popular psychology back to the original academic research tradition from which the claims were generated. It also addresses the conceptual and methodological controversies with respect to the original research typically ignored or played down in popular writing. This book covers a range of topics including the question of universal biases in judgment, resurgent notions of "fast" thinking and a cognitive unconscious, the psychology of happiness and other "positive" psychologies, the effects of parenting on child outcomes, and more general issues related to psychological tests and measures. The methodological problems that emerge include problems with generalizing from specific experimental conditions, highly biased sampling, lack of replication of findings, lack of shared referents across subfields, even different authors, as well as confusion around basic statistical and mathematical issues. Methodological Problems with the Academic Sources of Popular Psychology: Context, Inference, and Measurement reviews these issues extensively, offering both a sense of the history and pervasiveness of these issues in the field itself and an opportunity to review and master these difficult ideas.

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis. The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualising objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods using examples from various fields, with related R code accessible in the FactoMineR package developed by the authors.

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.

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.

In recent years, a psychological perspective has gained increasing acceptance in the education provided to musicians: teachers, performers, and "creatives" alike. Research in music psychology has revealed how musicians acquire the ability to convey emotional intentions as sounded music, how listeners perceive it as feelings and moods, and how this powerful process relates to social and cultural dynamics. Of course, people who identify as musicians have special interest in these matters. A well-cited volume ever since its initial publication in 2007, Psychology for Musicians is now brought up-to-date in a second edition, particularly in expanding outside the exclusive context of Western formal/academic settings. This new edition draws on insights from recent research in music psychology, combining academic rigor with accessibility to offer readers research-supported ideas that they can readily apply in their musical activities.

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.

Designing a research project is possibly the most difficult task a dissertation writer faces. It is fraught with uncertainty: what is the best subject? What is the best method? For every answer found, there are often multiple subsequent questions, so it's easy to get lost in theoretical debates and buried under a mountain of literature. This book looks at literature review in the process of research design, and how to develop a research practice that will build skills in reading and writing about research literature-skills that remain valuable in both academic and professional careers. Literature review is approached as a process of engaging with the discourse of scholarly communities that will help graduate researchers refine, define, and express their own scholarly vision and voice. This orientation on research as an exploratory practice, rather than merely a series of predetermined steps in a systematic method, allows the researcher to deal with the uncertainties and changes that come with learning new ideas and new perspectives. The focus on the practical elements of research design makes this book an invaluable resource for graduate students writing dissertations. Practicing research allows room for experiment, error, and learning, ultimately helping graduate researchers use the literature effectively to build a solid scholarly foundation for their dissertation research project.