This valuable book provides the student with a short, manageable, comprehensive guide to the Thematic Apperception Test (TAT), a major psychological measuring instrument. The TAT is effective in telling the clinician how the subject views the self and the world in his or her unique way. This sweeping introduction to this test as well as other lesser-known apperceptive techniques considers children, adolescents, and adults. and gives special attention to cross-cultural issues and the application of apperception techniques to minority populations. Additionally, the interesting history of apperception techniques, sample protocols, and the administration and interpretation of the tests are included.

This text introduces teachers to research methods they can use to examine their own classrooms in order to become more effective teachers. Becoming familiar with classroom-based research methods not only enables teachers to do research in their own classrooms, it also provides a basis for assessing the findings of existing research. McKay emphasizes throughout that what a teacher chooses to examine will dictate which method is most effective. Each chapter includes activities to help readers apply the methods described in the chapter, often by analyzing research data. *Chapter I, Classroom Research, introduces the reader to major research purposes and research types as they relate to classroom research, the distinction between quantitative and qualitative research, the formulation of research questions and research designs, and ethical issues in research. *Chapter II, Researching Teachers and Learners, presents research methods that can be used to examine teachers' and learners' attitudes and behaviors: action research, survey research, interviews, verbal reports, diary studies, case studies, and ethnographies. *Chapter III, Researching Classroom Discourse, deals with methods that can be used to study the oral and written discourse of classrooms: interaction analysis, discourse analysis, text analysis, and ways to examine the social and political assumptions underlying the choice and presentation of content in second language teaching materials. *Chapter IV, Writing Research Reports, provides guidelines for both thesis writing and journal articles. Researching Second Language Classrooms is an ideal text for TESOL research methods courses and an essential resource for inservice teachers who wish to undertake classroom research.

The Psychology Research Companion: From student project to working life not only gives you the skills and confidence to conduct your psychology research project at university, but is the first book to show how these skills will help you get ahead in your first job in the workplace. Jessica S. Horst, an American psychologist teaching in the UK, takes you through every step of the research process; from conceiving your research question and choosing a research methodology, to organizing your time and resources effectively. The book includes sections on ethics, data management, working with research participants and report writing, but each chapter is also informed by the wider aim of providing a toolkit for working life. Each chapter is packed with tips and skills that can be taken into the workplace, including working collaboratively and organising your workload, as well as discussing your research project in interview situations and when applying for jobs. This invaluable guide will appeal to all undergraduate and postgraduate psychology students whose aim is to learn a set of transferable research skills as well as to obtain a good degree result.

Test fairness is a moral imperative for both the makers and the users of tests. This book focuses on methods for detecting test items that function differently for different groups of examinees and on using this information to improve tests. Of interest to all testing and measurement specialists, it examines modern techniques used routinely to insure test fairness. Three of these relevant to the book's contents are: * detailed reviews of test items by subject matter experts and members of the major subgroups in society (gender, ethnic, and linguistic) that will be represented in the examinee population * comparisons of the predictive validity of the test done separately for each one of the major subgroups of examinees * extensive statistical analyses of the relative performance of major subgroups of examinees on individual test items.

This volume contains contributions from 24 internationally known scholars covering a broad spectrum of interests in cross-cultural theory and research. This breadth is reflected in the diversity of the topics covered in the volume, which include theoretical approaches to cross-cultural research, the dimensions of national cultures and their measurement, ecological and economic foundations of culture, cognitive, perceptual and emotional manifestations of culture, and bicultural and intercultural processes. In addition to the individual chapters, the volume contains a dialog among 14 experts in the field on a number of issues of concern in cross-cultural research, including the relation of psychological studies of culture to national development and national policies, the relationship between macro structures of a society and shared cognitions, the integration of structural and process models into a coherent theory of culture, how personal experiences and cultural traditions give rise to intra-cultural variation, whether culture can be validly measured by self-reports, the new challenges that confront cultural psychology, and whether psychology should strive to eliminate culture as an explanatory variable.

Half a century after the collapse of the Nazi regime and the Third Reich, scholars from a range of fields continue to examine the causes of Nazi Germany. An increasing number of young Americans are attempting to understand the circumstances that led to the rise of the Nazi party and the subsequent Holocaust, as well as the implication such events may have for today as the world faces a resurgence of neo-Nazism, ethnic warfare, and genocide. In the months following World War II, extensive psychiatric and psychological testing was performed on over 200 Nazis in an effort to understand the key personalities of the Third Reich and of those individuals who "just followed orders." In addressing these issues, the current volume examines the strange history of over 200 Rorschach Inkblot protocols that were administered to Nazi war criminals and answers such questions as: * Why the long delay in publishing protocols? * What caused such jealousies among the principals? * How should the protocols be interpreted? * Were the Nazis monsters or ordinary human beings? This text delivers a definitive and comprehensive study of the psychological functioning of Nazi war criminals -- both the elite and the rank-and-file. In order to apply a fresh perspective to understanding the causes that created such antisocial behavior, these analyses lead to a discussion within the context of previous work done in social and clinical psychology. Subjects discussed include the authoritarian personality, altruism, obedience to authority, diffusion of responsibility, and moral indifference. The implications for current political events are also examined as Neo-Nazism, anti-Semitism, and ethnic hate are once again on the rise. While the book does contain some technical material relating to the psychological interpretations, it is intended to be a scholarly presentation written in a narrative style. No prior knowledge of psychological testing is necessary, but it should be of great benefit for those interested in the Rorschach Inkblot test, or with a special interest in psychological testing, personality assessment, and the history of psychology. It is also intended for readers with a broad interest in Nazi Germany.

Test Scoring provides a summary of traditional true score test theory and modern item response theory related to scoring tests, as well as novel developments resulting from the integration of these approaches. The background material introduced in the first four chapters builds a foundation for the new developments covered in later chapters. These new methods offer alternative psychometric approaches to scoring complex assessments. Each of the book's contributors draws from the classic literature of traditional test theory, as well as psychometric developments of the past decade. The emphasis is on large-scale educational measurement but the topics and procedures may be applied broadly within many measurement contexts. Numerous graphs and illustrative examples based on real tests and actual data are integrated throughout. This multi-authored volume shows the reader how to combine the coded outcomes on individual test items into a numerical summary about the examinee's performance. This book is intended for researchers and students in education and other social sciences interested in educational assessment and policy, the design and development of tests, and the procedures for test administration and scoring. Prerequisites include an introduction to educational and psychological measurement and basic statistics. Knowledge of differential and integral calculus and matrix algebra is helpful but not required.

This book is an interdisciplinary guide to empirical research on nonverbal behaviour. It focuses on tools and procedures to investigate body movement and gesture and the relation to cognitive, emotional, and interactive processes. NEUROGES is an objective and reliable coding system for movement behaviour and gesture. Its combination with the multi-media annotation tool ELAN results in an effective movement analysis. Rater training and rating procedures constitute an important component in movement behaviour studies. A novel algorithm assesses interrater agreement for the segmentation of the ongoing flow of behaviour. Recommendations for study designs and statistical data evaluation are given, including innovative procedures for the analysis of interactive partners' body movements.

The amount of data in our world has been exploding, and analyzing large data sets-so called big data-will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.

In this book, William R. Uttal continues his analysis and critique of theories of mind. This book considers theories that are based on macroneural responses (such as those obtained from fMRI) that represent the averaged or cumulative responses of many neurons. The analysis is carried out with special emphasis on the logical and conceptual difficulties in developing a theory but with special attention to some of the current attempts to go from these cumulative responses to explanations of the grand question of how the mind is generated by the brain. While acknowledging the importance of these macroneural techniques in the study of the anatomy and physiology of the brain, Uttal concludes that this macroneural approach is not likely to produce a valid neural theory of cognition because the critical information-the states of the individual neurons-involved in brain activity becoming mental activity is actually lost in the process of summation. Controversial topics are considered in detail including discussions of empirical, logical, and technological barriers to theory building in cognitive neuroscience.

From Subject to Subjectivities profiles the recent debates about the role of qualitative and participatory methods in psychology, a discipline which has traditionally seen itself as a form of positivistic science. Contributors explain how fundamentally different views of the nature of reality and of scientific theory have shaped these debates, and how psychology is being transformed through the use of these methods.

At the heart of the book are 10 exemplars of interpretive and participatory action research which describe the rationale for and process of using these methods in actual cases. They also articulate some of the challenges psychologists may face in adopting them, offering insights into how these complications can be successfully negotiated. Relevant beyond psychology, the models provided can be used within the context of a wide array of social science disciplines, from sociology and anthropology to women's studies and public health.

The contributors represent a veritable "who's who" of qualitative scholars, including Lyn Mikel Brown, Larry Davidson, Michelle Fine, Louise Kidder, M. Brinton Lykes, Jeanne Marecek, Abigail Stewart, and Niobe Way.

No previous book has examined qualitative and participatory methods specifically within the context of psychology. From Subjects to Subjectivities provides a unique and badly needed resource for those interested in learning about the practice of these methods in the field.

This edited volume provides both conceptual and practical information for conducting and evaluating evidence-based outcome studies. It encompasses psychotherapy research for traditional mental health disorders (eg. depression, anxiety), as well as psychosocial-based treatments provided to medical patient populations to have impact either on the disease process itself (pain, cardiovascular risk) or to improve the quality of life of such individuals. This is a hands-on book, whose major emphasis is on the practical nuts-and-bolts implementation of psychosocial-based RCTs from conception to completion.

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.

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data. A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book's practical approach. The book provides sufficient conceptual background information to serve as a standalone text. Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

How Can You Improve Your Learning Capabilites? How Can You Enhance Your Potential for Change and Personal Growth? Most of us accept that education does not meet the needs of learners today, or their employers. This mismatch is a key reason why a high level of demotivated youth, as well as workers and managers remain unable to develop themselves. They have been other-organised and are unprepared for the world of work and the challenges of life. First published in 1991, this title offers a radical approach to human learning and personal change. Based on the reflective procedures of Learning Conversations, it enables a deep exploration of the learning process and allows individuals, teams and even whole organisations to create dynamic learning cultures capable of adaptive, constructive and continuing growth. Available again after some years this book is as relevant, if not of greater value, in our ever-changing society than when originally published.

This edited volume shows the relationship between dream research and its usefulness in treating patients. Milton Kramer and Myron Glucksman show that there is support for searching for the meaning of dream as experiences extended in time. Dreaming reflects psychological changes and is actually an orderly process, not a random experience. Several chapters in this book explore interviewing methodologies that will help clients reduce the frequency of their nightmares and thus contribute to successful therapy.

Choosing Methods in Mental Health Research develops a new framework for mental health research. It is concerned with how to choose the most appropriate mental health research method, not only to address a specific question, but to maximize the potential impact on shaping mental health care. Mike Slade and Stefan Priebe focus attention on the types of audience that the researcher is seeking to influence, the types of evidence each audience accepts as valid, and the relative strengths and limitations of each type of methodology. A range of research methodologies are described and critically appraised, and the use of evidence by different groups is discussed. This produces some important findings about the interplay between research production and consumption, and highlights directions for future mental health research theory and practice. The findings presented here will be relevant to mental health service users and professionals who use research evidence to inform decision-making. It will also prove an invaluable resource for students and researchers in the field of mental health.

Phil Fennell's tightly argued study traces the history of treatment of mental disorder in Britain over the last 150 years. He focuses specifically on treatment of mental disorder without consent within psychiatric practice, and on the legal position which has allowed it. Treatment Without Consent examines many controversial areas: the use of high-strength drugs and Electro Convulsive Therapy, physical restraint and the vexed issue of the sterilisation of people with learning disabilities. Changing notions of consent are discussed, from the common perception that relatives are able to consent on behalf of the patient, to present-day statutory and common law rules, and recent Law Commission recommendations. This work brings a complex and intriguing area to life; it includes a table of legal sources and an extensive bibliography. It is essential reading for historians, lawyers and all those who are interested in the treatment of mental disorder.

This celebrated primer presents an introduction to all of the key ingredients in understanding computerized adaptive testing technology, test development, statistics, and mental test theory. Based on years of research, this accessible book educates the novice and serves as a compendium of state-of-the-art information for professionals interested in computerized testing in the areas of education, psychology, and other related social sciences. A hypothetical test taken as a prelude to employment is used as a common example throughout to highlight this book's most important features and problems. Changes in the new edition include: *a completely rewritten chapter 2 on the system considerations needed for modern computerized adaptive testing; *a revised chapter 4 to include the latest in methodology surrounding online calibration and in the modeling of testlets; and *a new chapter 10 with helpful information on how test items are really selected, usage patterns, how usage patterns influence the number of new items required, and tools for managing item pools.

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.

Contributors to the volume represent an international "who's who" of research scientists from the fields of psychology and measurement. It offers the insights of these leading authorities regarding cognition and personality. In particular, they address the roles of constructs and values in clarifying the theoretical and empirical work in these fields, as well as their relation to educational assessment. It is intended for professionals and students in psychology and assessment, and almost anyone doing research in cognition and personality.

* It is a straightforward, conversational introduction to statistics that delivers exactly what its title promises. * Each chapter begins with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides. * Chapters also include an example of the statistic (or statistics) in use in real-world research, "Worked Examples," "Writing It Up" sections that demonstrate how to write about each statistic, "Wrapping Up and Looking Forward" sections, and practice work problems. * A new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added (Chapter 16). * Person-centered analysis is an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression) and is gaining popularity in social-science research. * The chapter on non-parametric statistics (Chapter 14) was enhanced significantly with in-depth descriptions of Mann-Whitney U, Kruskall-Wallace, and Wilcoxon Signed-Rank analyses. * These non-parametric statistics are important alternatives to statistics that rely on normally distributed data. * This new edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression (Chapter 13). * There is more information provided about the importance of the normal distribution in statistics (Chapters 4 and 7). * Each of the last nine chapters includes an example from the real world of research that employs the statistic, or statistics, covered in the chapter. * Altogether, these improvements provide important foundational information about how inferential statistics work and additional statistical tools that are commonly used by researchers in the social sciences. * The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.

This book covers statistical consequences of breaches of research integrity such as fabrication and falsification of data, and researcher glitches summarized as questionable research practices. It is unique in that it discusses how unwarranted data manipulation harms research results and that questionable research practices are often caused by researchers' inadequate mastery of the statistical methods and procedures they use for their data analysis. The author's solution to prevent problems concerning the trustworthiness of research results, no matter how they originated, is to publish data in publicly available repositories and encourage researchers not trained as statisticians not to overestimate their statistical skills and resort to professional support from statisticians or methodologists. The author discusses some of his experiences concerning mutual trust, fear of repercussions, and the bystander effect as conditions limiting revelation of colleagues' possible integrity breaches. He explains why people are unable to mimic real data and why data fabrication using statistical models stills falls short of credibility. Confirmatory and exploratory research and the usefulness of preregistration, and the counter-intuitive nature of statistics are discussed. The author questions the usefulness of statistical advice concerning frequentist hypothesis testing, Bayes-factor use, alternative statistics education, and reduction of situational disturbances like performance pressure, as stand-alone means to reduce questionable research practices when researchers lack experience with statistics.

The editors of this volume suggest that there are missing elements in the conceptualization upon which standard test theory is based. Those elements are models for just how people know what they know and do what they can do, and the ways in which they increase these capacities. Different models are useful for different purposes; therefore, broader or alternative student models may be appropriate. The chapters in this volume consider a variety of directions in which standard test theory might be extended. Topics covered include: the role of test theory in light of recent work in cognitive and educational psychology, test design, student modeling, test analysis, and the integration of assessment and instruction.

Although many archaeologists have a good understanding of the basics in computer science, statistics, geostatistics, modeling, and data mining, more literature is needed about the advanced analysis in these areas. This book aids archaeologists in learning more advanced tools and methods while also helping mathematicians, statisticians, and computer scientists with no previous knowledge of the field realize the potential of the methods in archaeological experiments.