The culmination of master psychiatrist Dr. Irvin D. Yalom’s more than thirty-five years in clinical practice, The Gift of Therapy is a remarkable and essential guidebook that illustrates through real case studies how patients and therapists alike can get the most out of therapy. The bestselling author of Love’s Executioner shares his uniquely fresh approach and the valuable insights he has gained—presented as eighty-five personal and provocative “tips for beginner therapists,” including:
•Let the patient matter to you
•Acknowledge your errors
•Create a new therapy for each patient
•Do home visits
•(Almost) never make decisions for the patient
•Freud was not always wrong
A book aimed at enriching the therapeutic process for a new generation of patients and counselors, Yalom’s Gift of Therapy is an entertaining, informative, and insightful read for anyone with an interest in the subject.
This rare memoir full of often raw details and emotions becomes an intimate conversation about the intricacies of feeling and relating in a relationship. What Ellis calls experimental ethnography is a finely crafted, forthright, and daring story framed by the author's reflections on writing about and analyzing one's own life. Casting off the safe distance of most social science inquiry, she surrenders the private shroud of a complex relationship to bring sociology closer to literature.
In recounting his patients' dilemmas, Yalom not only gives us a rare and enthralling glimpse into their personal desires and motivations but also tells us his own story as he struggles to reconcile his all-too human responses with his sensibility as a psychiatrist. Not since Freud has an author done so much to clarify what goes on between a psychotherapist and a patient.
Borderline personality disorder, autism, narcissism, psychosis, Asperger's: All of these syndromes have one thing in common--lack of empathy. In some cases, this absence can be dangerous, but in others it can simply mean a different way of seeing the world.In The Science of Evil Simon Baron-Cohen, an award-winning British researcher who has investigated psychology and autism for decades, develops a new brain-based theory of human cruelty. A true psychologist, however, he examines social and environmental factors that can erode empathy, including neglect and abuse.Based largely on Baron-Cohen's own research, The Science of Evil will change the way we understand and treat human cruelty.
This book attempts to understand normal social motives in murder as products of the process of evolution by natural selection. They note that the implications for psychology are many and profound, touching on such matters as parental affection and rejection, sibling rivalry, sex differences in interests and inclinations, social comparison and achievement motives, our sense of justice, lifespan developmental changes in attitudes, and the phenomenology of the self.
This is the first volume of its kind to analyze homicides in the light of a theory of interpersonal conflict. Before this study, no one had compared an observed distribution of victim-killer relationships to "expected" distribution, nor asked about the patterns of killer-victim age disparities in familial killings. This evolutionary psychological approach affords a deeper view and understanding of homicidal violence.
describes the history, development, and purposes of evocative storytelling;
provides detailed instruction on becoming a story-writer and living a writing life;
examines fundamental ethical issues, dilemmas, and responsibilities;
illustrates ways ethnography intersects with autoethnography;
calls attention to how truth and memory figure into the works and lives of evocative autoethnographers.
Schweigerts clear, succinct writing style, her focus on the fundamentals of research design, and her thorough coverage engage students who are at all levels of exposure to research methods. In the end, all students will learn to embrace the ethics and process of collecting and presenting useful, accurate data.
The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 .
Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
· Downloadable data sets
· Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more
· Additional material for data analysis
New to This Edition:
*Stronger discussion of different worldviews (e.g., constructivism, postpositivism, and pragmatism) and how they relate to different methodological choices.
*Clearer emphasis on doing a generalized qualitative study, while acknowledging 12 specialized genres (e.g., action-based research, arts-based research, autoethnography, grounded theory, phenomenology, and others).
*Expanded discussions of different kinds of qualitative study samples and of mixed methods.
*New ideas on how to avoid getting stalled when analyzing qualitative data.
*Consideration of an additional way of concluding a qualitative study: by taking action.
*Chapters start with an abstract and end with a suggested exercise.
*Key terms and concepts appear in boldface throughout the text and are listed in end-of-chapter recaps as well as in the book’s glossary.
*Sections within each chapter start with a preview box: “What you should learn from this section."
*An appendix presents a semester- or yearlong field-based project.
The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument.
Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.
*An exemplar journal article at the end of each methods chapter, together with questions and activities for critiquing it (including, where applicable, checklist forms to identify threats to internal and external validity), plus lists of additional research examples.
*Research example boxes showing how studies are designed to address particular research questions.
*In every chapter: numbered chapter objectives, bulleted summaries, subheadings written as questions, a running glossary, and end-of-chapter discussion questions.
* Electronic Instructor's Resource Manual with Test Bank, provided separately--includes chapter outlines; answers to exercises, discussion questions, and illustrative example questions; and PowerPoints.
*"Let's Start Writing" exercises leading up to a complete proposal draft.
*"Do You Understand?" checklists of key terms plus an end-of-book glossary.
*End-of-chapter quizzes with answers.
*Case study examples from education, psychology, health sciences, business, and information systems.
*Sample proposal with three variants of the methods chapter: quantitative, qualitative, and mixed methods.
New features in the fourth edition include:
sets of work problems in each chapter with detailed solutions and additional problems online to help students test their understanding of the material,
new "Worked Examples" to walk students through how to calculate and interpret the statistics featured in each chapter,
new examples from the author’s own data and from published research and the popular media to help students see how statistics are applied and written about in professional publications,
many more examples, tables, and charts to help students visualize key concepts, clarify concepts, and demonstrate how the statistics are used in the real world.
a more logical flow, with correlation directly preceding regression, and a combined glossary appearing at the end of the book,
a Quick Guide to Statistics, Formulas, and Degrees of Freedom at the start of the book, plainly outlining each statistic and when students should use them,
greater emphasis on (and description of) effect size and confidence interval reporting, reflecting their growing importance in research across the social science disciplines
an expanded website at www.routledge.com/cw/urdan with PowerPoint presentations, chapter summaries, a new test bank, interactive problems and detailed solutions to the text’s work problems, SPSS datasets for practice, links to useful tools and resources, and videos showing how to calculate statistics, how to calculate and interpret the appendices, and how to understand some of the more confusing tables of output produced by SPSS.
Statistics in Plain English, Fourth Editionis an ideal guide for statistics, research methods, and/or for courses that use statistics taught at the undergraduate or graduate level, or as a reference tool for anyone interested in refreshing their memory about key statistical concepts. The research examples are from psychology, education, and other social and behavioral sciences.
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.
New to the Third Edition
Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code
The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
• The 15 chapters cover 191 guidelines for effective scientific writing. The guidelines are fully illustrated with easy-to-follow examples.
• The guidelines describe the types of information that should be included, how this information should be expressed, and where various types of information should be placed within a research report.
• End-of-chapter questions help students master the writing process.
• Most chapters are conveniently divided into easy-to-follow guidelines, sequential steps, or checklists. Numerous examples throughout the book show students what should and should not be done when writing reviews.
• Emphasizes critical analysis of reports of empirical research in academic journals—making it ideal as a supplement for research methods courses. This book makes it possible for students to work independently on a critical literature review as a term project.
• Nine model literature reviews at the end of the book provide the stimulus for homework assignments and classroom discussions.
• The activities at the end of each chapter keep students moving toward their goal of writing a polished, professional review of academic literature.
• Most examples include material from recently published research. Includes nine model literature reviews for discussion and evaluation.
After reviewing both our practical and theoretical research, and focusing on Jung's theory as to the influence of the collective unconscious on individual human psyche, it would be essential to examine this issue from the standpoint of the psychology of individual distinctions. It's obvious that without finding individual archetypal patterns as the basis for human personality, solving any individual or social-collective problems wouldn't be possible since any society consists of individuals constantly affecting one another.
Download PDF at http://www.humanpopulationacademy.org/uploads/publications/FromCarlGustavJungArchetypesOfTheCollectiveUnconsciousToIndividualArchetypalPatterns.pdf
New to the seventh edition:
Each chapter breaks down the larger holistic review of literature exercise into a series of smaller, manageable steps
Practical instructions for navigating today’s digital libraries
Comprehensive discussions about digital tools, including bibliographic and plagiarism detection software
Chapter activities that reflect the book’s updated content
New model literature reviewsOnline resources designed to help instructors plan and teach their courses (www.routledge.com/9780415315746).
Twenty-three characteristics shared by jailed violent criminals are analyzed and considered in terms of neuropsychology and developmental psychology. The book also probes psychopathy in its various degrees, in children, adolescents, and adults, and explains a controversial but increasingly accepted theory that psychopathy is a "natural" outgrowth of evolution, describing how this "natural" psychopathy can become a condition typified by violent, sadistic, and irreversible personality disorder.
• Your students will learn the practical aspects of evaluating research, not just how to apply a laundry list of technical terms from their textbooks.
• Each chapter is organized around evaluation questions. For each question, there is a concise explanation of how to apply it in the evaluation of research reports.
• Numerous examples from journals in the social and behavioral sciences illustrate the application of the evaluation questions. Students see actual examples of strong and weak features of published reports.
• Commonsense models for evaluation combined with a lack of jargon make it possible for students to start evaluating research articles the first week of class.
• The structure of this book enables students to work with confidence while evaluating articles for homework.
• Avoids oversimplification in the evaluation process by describing the nuances that may make an article publishable even though it has serious methodological flaws. Students learn when and why certain types of flaws may be tolerated. They learn why evaluation should not be performed mechanically.
• This book received very high student evaluations when field-tested with students just beginning their study of research methods.
• Contains more than 60 new examples from recently published research. In addition, minor changes have been made throughout for consistency with the latest edition of the Publication Manual of the American Psychological Association.
This comprehensive treatment of single-subject or within-subject design focuses on the strategic (the overall goal) and tactical (the methods and procedures) options available to investigators as they try to determine the most effective way of addressing research questions. The authors guide readers to consider the rationale for different ways of measuring behavior and designing experimental comparisons. At every point, the text explains the strengths and weaknesses of alternative choices so that readers can make the best decision in each situation.
Highlights of the new third edition include:Rewritten in a straightforward and accessible style for students without a background in this area, this edition features many more field-based examples and applications. Increased focus on the application of research methods to the needs of practitioners in measuring behavior change and evaluating interventions under field conditions. Increased use of learning aids, including a "built-in study guide," summary tables, figures, boxed discussions of special topics, key terms with definitions, chapter summaries, suggested readings, discussion questions and exercises, and a glossary. Instructor’s resource materials available on a password-protected website with digital access to figures, tables, definition of new terms by chapters, multiple choice test questions, and content from the book’s learning aids, including study guide questions and suggested topics for class discussion and exercises.
With a focus on direct behavioral measurement and within-subject design, this book is intended for advanced undergraduate or graduate courses in behavioral research methods, basic or applied behavior analysis, or single-/within-subject design taught in psychology (especially clinical and counseling psychology), social work, education, developmental disabilities, and other social and health science programs that deal with human behavior in research or practice settings. Although the book is written for students without a background in behavioral research, its comprehensive approach to designing procedures for measuring behavior and creating experimental comparisons also make it a valuable resource for investigators and professionals.
•Lively examples on contemporary topics stimulate students’ interest and show the relevance of research methods to their everyday lives.
•Divided into short sections, this book makes it easy for you to give customized assignments. Assign only the sections your students need.
•Shows students how to interpret statistics without computations.
•Factual Questions at the end of each section allow students to check their comprehension.
•Questions for Discussion stimulate classroom dialogue.
• New to this edition: Five new sections on in-text citations and reference lists have been added. Numerous changes have also been made for consistency with the latest editions of the APA and ASA Style manuals, and new examples have been added.
• 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.
From the Trade Paperback edition.
*Winner of the 2014 Distinguished Publication Award (DPA) from the Association for Women in Psychology (AWP)*
Successful Qualitative Research: A Practical Guide for Beginners is an accessible, practical textbook. It sidesteps detailed theoretical discussion in favor of providing a comprehensive overview of strategic tips and skills for starting and completing successful qualitative research.
Uniquely, the authors provide a "patterns framework" to qualitative data analysis in this book, also known as "thematic analysis." The authors walk students through a basic thematic approach, and compare and contrast this with other approaches. This discussion of commonalities, explaining why and when each method should be used, and in the context of looking at patterns, will provide students with complete confidence for their qualitative research journey.
This textbook will be an essential textbook for undergraduates and postgraduates taking a course in qualitative research or using qualitative approaches in a research project.
Electronic Inspection Copy available for instructors here.
The twenty chapters address such subjects as gay political language, homosexuality and AIDS on prime-time television, the politics of male homosexuality in young adult fiction, the identification of female athleticism with lesbianism, the politics of identity in the works of Edmund White, and coming out strategies. This is must reading for students of communication practices and theory, and for everyone interested in human sexuality.
Contributing to the book are: James Chesebro (Indiana State), James Darsey (Ohio State), Joseph A. Devito (Hunter College, CUNY), Timothy Edgar (Purdue), Mary Anne Fitzpatrick (Wisconsin, Madison), Karen A. Foss (Humboldt State), Kirk Fuoss (St. Lawrence), Larry Gross (Pennsylvania), Darlene Hantzis (Indiana State), Fred E. Jandt (California State, San Bernardino), Mercilee Jenkins (San Francisco State), Valerie Lehr (St. Lawrence), Lynn C. Miller (Texas, Austin), Marguerite Moritz (Colorado, Boulder), Fred L. Myrick (Spring Hill), Emile Netzhammer (Buffalo State), Elenie Opffer, Dorothy S. Painter (Ohio State), Karen Peper (Michigan), Nicholas F. Radel (Furman), R. Jeffrey Ringer (St. Cloud State), Scott Shamp (Georgia), Paul Siegel (Gallaudet), Jacqueline Taylor (Depaul), Julia T. Wood (North Carolina, Chapel Hill).
• All major statistical techniques covered in beginning statistics classes are included:
· descriptive statistics
· graphing data
· prediction and association
· parametric inferential statistics
· nonparametric inferential statistics
· statistics for test construction
• Each section starts with a brief description of the statistic that is covered and important underlying assumptions, which help students select appropriate statistics.
• Each section describes how to interpret results and express them in a research report after the data are analyzed. For example, students are shown how to phrase the results of a significant and an insignificant t test.
• More than 200 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS.
• A glossary of statistical terms is included, which makes a handy reference for students who need to review the meanings of basic statistical terms.
• Practice exercises throughout the book give students stimulus material to use as they practice to achieve mastery of the program.
• Thoroughly field-tested; your students are certain to appreciate this book.
This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.
Max van Manen is the editor of the series Phenomenology of Practice, https://www.routledge.com/series/PPVM
• Clear and to-the-point narrative makes this short book perfect for all courses in which statistics are discussed.
• Helps statistics students who are struggling with the concepts. Shows them the meanings of the statistics they are computing.
• This book is easy to digest because it is divided into short sections with review questions at the end of each section.
• Running sidebars draw students’ attention to important concepts.
-Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data.
-Exercises with an answer key allow readers to practice the skills they learn.
-Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences.
-Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts.
-Point to Rememberboxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts.
Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9.
Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.
This book offers a step-by-step guide to using MATLAB with Psychtoolbox to create customisable experiments. Its pocket size and simple language allow you to get straight to the point and help you to learn fast in order to complete your work in great time. In nine simple steps, it guides you all the way from setting parameters for your experiment to analysing the output. Gone are the daunting days of working through hundreds of irrelevant and complicated documents, as in this handy book, Erman Misirlisoy coaxes you in the right direction with his friendly and encouraging tricks and tips.
If you want to learn how to develop your own experiments to collect and analyse behavioral data, then this book is a must-read. Whether you are a student in experimental psychology, a researcher in cognitive neuroscience, or simply someone who wants to run behavioral tasks on your friends for fun, this book will offer you the skills to succeed.
The first part of the book carefully examines the research past and present regarding clinical, psychological, societal, and biological bases for violent behavior, specific to the serial murderer. Part two establishes a novel theory of the pattern of violence and then explores this hypothesis through eight case studies, interviews with serial killers, and elemental analysis. The work also contains a chapter based on conversations between the author and a convicted serial murderer.
After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. For those new to R, the appendix provides an introduction to this system that covers basic R knowledge necessary to run the models in the book.
Through the R code and detailed explanations provided, this book gives you the tools to launch your own investigations in multilevel modeling and gain insight into your research.
*Multiple "Review Stops" in each chapter--quick quizzes with answer keys.
*End-of-chapter writing exercises, research activities, and suggested resources.
*Bold-face key terms and an end-of-book glossary.
*Boxed tips from experts in the respective approaches.
*Supplemental PowerPoint slides for instructors using the book in a class.
The new edition features:
Updated to IBM SPSS version 20 but the book can also be used with older and newer versions of SPSS. A new chapter (7) including an introduction to Cronbach’s alpha and factor analysis. Updated Web Resources with PowerPoint slides, additional activities/suggestions, and the answers to even-numbered interpretation questions for the instructors, and chapter study guides and outlines and extra SPSS problems for the students. The web resource is located www.routledge.com/9781848729827 . Students, instructors, and individual purchasers can access the data files to accompany the book at www.routledge.com/9781848729827 .
IBM SPSS for Introductory Statistics, Fifth Editionprovides helpful teaching tools:
All of the key IBM SPSS windows needed to perform the analyses. Complete outputs with call-out boxes to highlight key points. Flowcharts and tables to help select appropriate statistics and interpret effect sizes. Interpretation sections and questions help students better understand and interpret the output. Assignments organized the way students proceed when they conduct a research project. Examples of how to write about outputs and make tables in APA format. Helpful appendices on how to get started with SPSS and write research questions.
An ideal supplement for courses in either statistics, research methods, or any course in which SPSS is used, such as in departments of psychology, education, and other social and health sciences. This book is also appreciated by researchers interested in using SPSS for their data analysis.