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Books > Social sciences > Psychology > Psychological methodology
Appreciation of the beauty and complexity of the human mind when perceiving an ambiguous stimulus led Dr. Hermann Rorschach to develop his scientific method eighty years ago. Full of gratitude for his brief life and work, the editors hope this volume will stand as an idiographic testament to his brilliance for the Rorschach students of the future. The contributors are clearly the most notable Rorschach clinicians in practice, and their work integrates the Comprehensive System and psychoanalytic methods. This book is organized into four sections. Within each of the first three sections -- devoted to psychotic, borderline, and neurotic disorders respectively -- the editors and invited authors have contributed Rorschach case studies which vertically cut a character pathology, personality disorder, or clinical diagnosis through a particular level of personality organization. The last section charts the enormously varied course that Rorschach work can navigate -- from the understanding of a Nobel laureate, the pain of trauma and transexuality, and the Nazi perversion of youth, to the consensus Rorschach in couple's therapy and cutting edge work in neuropsychology.
Devising tests that evaluate a nation's educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design. The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST. Intended for psychologists, social scientists, and educational measurement scientists, this volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions. Winner of the 2016 AERA Award for Significant Contribution to Educational Measurement and Research Methodology The 2016 American Education Research Association (AERA) Div. D award committee for Significant Contributions to Educational Measurement and Research Methodology has recognized unanimously this collaborative work advancing the theory and applications of computerized MST. This annual award recognizes published research judged to represent a significant conceptual advancement in the theory and practice of educational measurement and/or educational research methodology. The 2016 award was made under the heading: Measurement, Psychometrics, and Assessment. This collective work, published in 2014 as an edited volume titled Computerized Multistage Testing: Theory and Applications, was cited by the committee both for the originality of the conceptual foundations presented in support of multistage testing and for arguing persuasively for its potential impact on the practice of educational measurement.
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors' collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book's web page.
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.
Since the mid-80s several laboratories around the world have been developing techniques for the operational use of tests derived from item-generation. According to the experts, the major thrust of test development in the next decade will be the harnessing of item generation technology to the production of computer developed tests. This is expected to revolutionize the way in which tests are constructed and delivered. This book is a compilation of the papers presented at a symposium held at ETS in Princeton, attended by the world's foremost experts in item-generation theory and practice. Its goal is to present the major applications of cognitive principles in the construction of ability, aptitude, and achievement tests. It is an intellectual contribution to test development that is unique, with great potential for changing the ways tests are generated. The intended market includes professional educators and psychologists interested in test generation.
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.
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.
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.
This new volume is the first to focus entirely on automated essay scoring and evaluation. It is intended to provide a comprehensive overview of the evolution and state-of-the-art of automated essay scoring and evaluation technology across several disciplines, including education, testing and measurement, cognitive science, computer science, and computational linguistics. The development of this technology has led to many questions and concerns. Automated Essay Scoring attempts to address some of these questions including: *How can automated scoring and evaluation supplement classroom instruction? *How does the technology actually work? *Can it improve students' writing? *How reliable is the technology? *How can these computing methods be used to develop evaluation tools? *What are the state-of the-art essay evaluation technologies and automated scoring systems? Divided into four parts, the first part reviews the teaching of writing and how computers can contribute to it. Part II analyzes actual automated essay scorers including e-raterTM, Intellimetric, and the Intelligent Essay Assessor. The third part analyzes related psychometric issues, and the final part reviews innovations in the field. This book is ideal for researchers and advanced students interested in automated essay scoring from the fields of testing and measurement, education, cognitive science, language, and computational linguistics.
Since the early days of performance assessment, human ratings have been subject to various forms of error and bias. Expert raters often come up with different ratings for the very same performance and it seems that assessment outcomes largely depend upon which raters happen to assign the rating. This book provides an introduction to many-facet Rasch measurement (MFRM), a psychometric approach that establishes a coherent framework for drawing reliable, valid, and fair inferences from rater-mediated assessments, thus answering the problem of fallible human ratings. Revised and updated throughout, the Second Edition includes a stronger focus on the Facets computer program, emphasizing the pivotal role that MFRM plays for validating the interpretations and uses of assessment outcomes.
This book provides a definitive empirical study of antisocial character pathology and its assessment through the use of the Rorschach. Drawing upon a decade of research with nearly 400 individuals in various hospitals and prisons, the authors paint an extraordinary intrapsychic picture of the personality structure and psychodynamics of these troublesome patients. Serving as both an educational tool and a reference text, this book presents: * Rorschach data on several different antisocial groups -- conduct disordered children and adolescents, antisocial personality disordered adult males with and without schizophrenia, antisocial adult females, and male and female sexual homicide perpetrators; * nomothetic (group) and idiographic (case study) data; * data which have been analyzed and theoretically interpreted using both structural methods and psychoanalytic approaches which represent the cutting edge of Rorschach theory and practice; and * a developmental approach in analyzing Rorschach data gathered from antisocial children, adolescents, and adults -- providing striking similarities. This is the first Rorschach database of this type that has ever been published. As such, it serves as a valuable reference text for Rorschach users -- providing a definitive empirical base, theoretical integration, and a focus on individuals who create severe problems for society.
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.
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.
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.
In this collection, international contributors come together to discuss how qualitative and quantitative methods can be used in psychotherapy research. The book considers the advantages and disadvantages of each approach, and recognises how each method can enhance our understanding of psychotherapy. Divided into two parts, the book begins with an examination of quantitative research and discusses how we can transfer observations into numbers and statistical findings. Chapters on quantitative methods cover the development of new findings and the improvement of existing findings, identifying and analysing change, and using meta-analysis. The second half of the book comprises chapters considering how qualitative and mixed methods can be used in psychotherapy research. Chapters on qualitative and mixed methods identify various ways to strengthen the trustworthiness of qualitative findings via rigorous data collection and analysis techniques. Adapted from a special issue of Psychotherapy Research, this volume will be key reading for researchers, academics, and professionals who want a greater understanding of how a particular area of research methods can be used in psychotherapy.
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.
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.
This training book is designed to help professionals enhance their knowledge of community quality-of-life indicators, and to develop viable community projects. Chapter 1 describes the theoretical concepts that guide the formulation of community indicator projects. Chapter 2 creates a sample community indicator project as a template of the entire process. Chapter 3 describes the planning process: how to identify sponsors, secure funding, develop an organizational structure, select a quality-of-life model, select indicators, and so on. Chapter 4 focuses on data collection. Finally, Chapter 5 describes efforts related to dissemination and promotion of community indicators projects. Written by a stalwart in the field of quality-of-life research, this book provides the tools of sound community project planning for quality-of-life researchers, social workers, social marketers, community research organizations, and policy-makers.
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.
Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book's coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.
Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo methods. It includes discussions on issues related to statistical theory, numerical methods, and the mechanics of computer programs for parameter estimation, which help to build a clear understanding of the computational demands and challenges of IRT estimation procedures.
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.
This book will help readers understand the practice of qualitative research--whether they want to do it, teach it, or just learn about it. All the major research phases are encompassed (startup, design, data collection, analysis, and composing), including newly emerging trends. Numerous easy-to-read vignettes show how other scholars have successfully implemented specific procedures. Equally distinctive, the book presents qualitative research as an adaptive craft. The array of choices among different procedures and methods enables readers to customize their own studies and to accommodate different worldviews and genres. 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. Pedagogical Features *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. |
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