Transforming the Measurement of Learning and Teaching in Higher Education proposes a dynamic new model for educational measurement by reconceptualizing the field of learning analytics. Revolving around the agency and daily work of those in the field, this book describes how colleges and universities can be better structured for quality learning, showcases new tools for gathering emergent feedback, and demonstrates how that feedback can be used effectively across higher education organizations. Leaders and practitioners at all levels are offered new approaches for organizational and technological design that ensure the type of data and the way it is gathered serve the ultimate goal of high quality learning and teaching.

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

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

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

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences. Enrolling in their first statistics course, students are often apprehensive or extremely anxious toward the subject matter. And while IBM SPSS is one of the more easy-to-use statistical software programs available, for anxious students who realize they not only have to learn statistics but also new software, the task can seem insurmountable. Keenly aware of students' anxiety with statistics (and the fact that this anxiety can affect performance), Ronald D. Yockey has written SPSS Demystified: A Simple Guide and Reference, now in its fourth edition. Through a comprehensive, step-by-step approach, this text is consistently and specifically designed to both alleviate anxiety toward the subject matter and build a successful experience analyzing data in SPSS. Topics covered in the text are appropriate for most introductory and intermediate statistics and research methods courses. Key features of the text: Step-by-step instruction and screenshots Designed to be hands-on with the user performing the analyses alongside on their computer as they read through each chapter Call-out boxes provided, highlighting important information as appropriate SPSS output explained, with written results provided using the popular, widely recognized APA format End-of-chapter exercises included, allowing for additional practice SPSS datasets available on the publisher's website New to the Fourth Edition: Fully updated to SPSS 28 Updated screenshots in full color to reflect changes in SPSS software system (version 28) Exercises updated with up-to-date examples Exact p-values provided (consist with APA recommendations)

Originally published in 1979, this title represents a summary of 17 years of research centring around the Sensation Seeking Scale (SSS) and the theory from which the test was derived. Now an integral part of personality testing, including adaptations for use with children, this reissue is a chance to see where it all began.

Developmental evaluation (DE) offers a powerful approach to monitoring and supporting social innovations by working in partnership with program decision makers. In this book, eminent authority Michael Quinn Patton shows how to conduct evaluations within a DE framework. Patton draws on insights about complex dynamic systems, uncertainty, nonlinearity, and emergence. He illustrates how DE can be used for a range of purposes: ongoing program development, adapting effective principles of practice to local contexts, generating innovations and taking them to scale, and facilitating rapid response in crisis situations. Students and practicing evaluators will appreciate the book's extensive case examples and stories, cartoons, clear writing style, "closer look" sidebars, and summary tables. Provided is essential guidance for making evaluations useful, practical, and credible in support of social change. See also Developmental Evaluation Exemplars, edited by Michael Quinn Patton, Kate McKegg, and Nan Wehipeihana, which presents 12 in-depth case studies.

Prepares readers to analyze data and interpret statistical results using the increasingly popular R more quickly than other texts through LessR extensions which remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming first. Readers can select the necessary procedure and change the relevant variables without programming. Quick Starts introduce readers to the concepts and commands reviewed in the chapters. Margin notes define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output. Numerous examples of output from psychology, business, education, and other social sciences demonstrate how to interpret results and worked problems help readers test their understanding. www.lessRstats.com website features the lessR program, the book's 2 data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book's worked problems, links to R/lessR videos to help readers better understand the program, and more. New to this edition: o upgraded functionality and data visualizations of the lessR package, which is now aesthetically equal to the ggplot 2 R standard o new features to replace and extend previous content, such as aggregating data with pivot tables with a simple lessR function call.

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.

Signal detection theory--as developed in electrical engineering and based on statistical decision theory--was first applied to human sensory discrimination 40 years ago. The theoretical intent was to provide a valid model of the discrimination process; the methodological intent was to provide reliable measures of discrimination acuity in specific sensory tasks. An analytic method of detection theory, called the relative operating characteristic (ROC), can isolate the effect of the placement of the decision criterion, which may be variable and idiosyncratic, so that a pure measure of intrinsic discrimination acuity is obtained. For the past 20 years, ROC analysis has also been used to measure the discrimination acuity or inherent accuracy of a broad range of practical diagnostic systems. It was widely adopted by methodologists in the field of information retrieval, is increasingly used in weather forecasting, and is the generally preferred method in clinical medicine, primarily in radiology. This book attends to both themes, ROC analysis in the psychology laboratory and in practical diagnostic settings, and to their essential unity. The focus of this book is on detection and recognition as fundamental tasks that underlie most complex behaviors. As defined here, they serve to distinguish between two alternative, confusable stimulus categories, which may be perceptual or cognitive categories in the psychology laboratory, or different states of the world in practical diagnostic tasks. This book on signal detection theory in psychology was written by one of the developers of the theory, who co-authored with D.M. Green the classic work published in this area in 1966 (reprinted in 1974 and 1988). This volume reviews the history of the theory in engineering, statistics, and psychology, leading to the separate measurement of the two independent factors in all discrimination tasks, discrimination acuity and decision criterion. It extends the previous book to show how in several areas of psychology--in vigilance and memory--what had been thought to be discrimination effects were, in reality, effects of a changing criterion. The book shows that data plotted in terms of the relative operating characteristic have essentially the same form across the wide range of discrimination tasks in psychology. It develops the implications of this ROC form for measures of discrimination acuity, pointing up the valid ones and identifying several common, but invalid, ones. The area under the binormal ROC is seen to be supported by the data; the popular measures d' and percent correct are not. An appendix describes the best, current programs for fitting ROCs and estimating their parameters, indices, and standard errors. The application of ROC analysis to diagnostic tasks is also described. Diagnostic accuracy in a wide range of tasks can be expressed in terms of the ROC area index. Choosing the appropriate decision criterion for a given diagnostic setting--rather than considering some single criterion to be natural and fixed--has a major impact on the efficacy of a diagnostic process or system. Illustrated here by separate chapters are diagnostic systems in radiology, information retrieval, aptitude testing, survey research, and environments in which imminent dangerous conditions must be detected. Data from weather forecasting, blood testing, and polygraph lie detection are also reported. One of these chapters describes a general approach to enhancing the accuracy of diagnostic systems.

The crux of the debate between proponents of behavioral psychology and cognitive psychology focuses on the issue of accessibility. Cognitivists believe that mental mechanisms and processes are accessible, and that their inner workings can be inferred from experimental observations of behavior. Behaviorists, on the contrary, believe that mental processes and mechanisms are inaccessible, and that nothing important about them can be inferred from even the most cleverly designed empirical studies. One argument that is repeatedly raised by cognitivists is that even though mental processes are not directly accessible, this should not be a barrier to unravelling the nature of the inner mental processes and mechanisms. Inference works for other sciences, such as physics, so why not psychology? If physics can work so successfully with their kind of inaccessibility to make enormous theoretical progress, then why not psychology? As with most previous psychological debates, there is no "killer argument" that can provide an unambiguous resolution. In its absence, author William Uttal explores the differing properties of physical and psychological time, space, and mathematics before coming to the conclusion that there are major discrepancies between the properties of the respective subject matters that make the analogy of comparable inaccessibilities a false one.

See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB (R) routines used for the examples are available on the authors' website. The book provides you with the essential background on latent variable models, particularly the latent class model. It discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the assumptions of the basic version of the latent Markov model and introduce maximum likelihood estimation through the Expectation-Maximization algorithm. They also cover constrained versions of the basic latent Markov model, describe the inclusion of the individual covariates, and address the random effects and multilevel extensions of the model. After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference. As longitudinal data become increasingly relevant in many fields, researchers must rely on specific statistical and econometric models tailored to their application. A complete overview of latent Markov models, this book demonstrates how to use the models in three types of analysis: transition analysis with measurement errors, analyses that consider unobserved heterogeneity, and finding clusters of units and studying the transition between the clusters.

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data. New to the Second Edition Reorganized to focus on unbalanced data Reworked balanced analyses using methods for unbalanced data Introductions to nonparametric and lasso regression Introductions to general additive and generalized additive models Examination of homologous factors Unbalanced split plot analyses Extensions to generalized linear models R, Minitab (R), and SAS code on the author's website The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author's accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists - examples and claimed prevalence Why the Misconception is Dangerous - consequence of having the misunderstanding Undoing the Misconception - how to think correctly about the concept Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception. The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook. An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.

Originally published in 1987, this book presents papers from the First Conference of European Clinical Psychologists, held at the University of Kent Canterbury in July of that year. It shows some of the most exciting and recent developments in research and innovations in professional practice from many European countries with an overall theme of the WHO strategy of 'Health for all by the year 2000.' The whole range of clinical psychology is covered, including: cognitive therapy, clinical psychology and WHO strategy, the mental health of ethnic minority groups, health psychology, care in the community, and many other topics. The book is likely to be of interest for anyone concerned with the recent history and policies in clinical psychology.

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.