The general theme of this book is to present innovative psychometric modeling and methods. In particular, this book includes research and successful examples of modeling techniques for new data sources from digital assessments, such as eye-tracking data, hint uses, and process data from game-based assessments. In addition, innovative psychometric modeling approaches, such as graphical models, item tree models, network analysis, and cognitive diagnostic models, are included. Chapters 1, 2, 4 and 6 are about psychometric models and methods for learning analytics. The first two chapters focus on advanced cognitive diagnostic models for tracking learning and the improvement of attribute classification accuracy. Chapter 4 demonstrates the use of network analysis for learning analytics. Chapter 6 introduces the conjunctive root causes model for the understanding of prerequisite skills in learning. Chapters 3, 5, 8, 9 are about innovative psychometric techniques to model process data. Specifically, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8 discusses the modeling approach of hint uses and response accuracy in learning environment. Chapter 9 demonstrates the identification of observable outcomes in the game-based assessments. Chapters 7 and 10 introduce innovative latent variable modeling approaches, including the graphical and generalized linear model approach and the dynamic modeling approach. In summary, the book includes theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to model and analyze multiple data sources from digital assessments. When computer-based assessments are emerging and evolving, it is important that researchers can expand and improve the methods for modeling and analyzing new data sources. This book provides a useful resource to researchers who are interested in the development of psychometric methods to solve issues in this digital assessment age.

* Provides an up to date reference point for ethnographic research conducted into healthcare research * Embodies an outline of major methodological approaches to health and well-being ethnography * Includes illustrative case-studies of ethnographical research within the healthcare setting. * Offers a holistic view of ethnography, taking a multi-disciplinary approach

* Provides an up to date reference point for ethnographic research conducted into healthcare research * Embodies an outline of major methodological approaches to health and well-being ethnography * Includes illustrative case-studies of ethnographical research within the healthcare setting. * Offers a holistic view of ethnography, taking a multi-disciplinary approach

Measurement Theory in Action, Third Edition, helps readers apply testing and measurement theories and features 22 self-contained modules which instructors can match to their courses. Each module features an overview of a measurement issue and a step-by-step application of that theory. Best Practices provide recommendations for ensuring the appropriate application of the theory. Practical Questions help students assess their understanding of the topic. Students can apply the material using real data in the Exercises, some of which require no computer access, while others involve the use of statistical software to solve the problem. Case Studies in each module depict typical dilemmas faced when applying measurement theory followed by Questions to Ponder to encourage critical examination of the issues noted in the cases. The book's website houses the data sets, additional exercises, PowerPoints, and more. Other features include suggested readings to further one's understanding of the topics, a glossary, and a comprehensive exercise in Appendix A that incorporates many of the steps in the development of a measure of typical performance. Updated throughout to reflect recent changes in the field, the new edition also features: Recent changes in understanding measurement, with over 50 new and updated references Explanations of why each chapter, article, or book in each module's Further Readings section is recommended Instructors will find suggested answers to the book's questions and exercises; detailed solutions to the exercises; test bank with 10 multiple choice and 5 short answer questions for each module; and PowerPoint slides. Students and instructors can access SPSS data sets; additional exercises; the glossary; and additional information helpful in understanding psychometric concepts. It is ideal as a text for any psychometrics or testing and measurement course taught in psychology, education, marketing, and management. It is also an invaluable reference for professional researchers in need of a quick refresher on applying measurement theory.

Hierdie handboek verskaf 'n inleiding tot sielkundige en opvoedkundige meting aan die hand van Suid-Afrikaanse voorbeelde. Die bespreking van plaaslik ontwikkelde meetinstrumente is nie ensiklopedies nie, maar is eerder bedoel om die beginsels onderliggend aan meting te illustreer. Die bekendste en mees gebruikte Suid-Afrikaanse toetse word behandel. Onderwerpe van 'n meer tegniese aard word oppervlakkig gedek, en daar word aanvaar dat die leser vertroud is met die elementere begrippe uit die beskrywende statistiek.

In this book, Hackett introduces the traditional usage of the mapping sentence within quantitative research, reviews its philosophical underpinnings, and proposes the "declarative mapping sentence" as an instrument and approach to qualitative scholarship. With a helpful glossary and a range of illustrative tables, Hackett takes the reader through a straightforward introduction to mapping sentences and their construction, before discussing declarative mapping sentences and possible future research directions. This innovative direction for social research provides a flexible structure for research domain, and it allows qualitative research results to be uniformly sorted. Declarative Mapping Sentences in Qualitative Research will be essential reading for researchers, academics, and postgraduate students in the fields of qualitative psychology and psychological methods, as well as philosophical psychology and social science research methods.

This book critically examines the work of a number of pioneers of social psychology, including legendary figures such as Kurt Lewin, Leon Festinger, Muzafer Sherif, Solomon Asch, Stanley Milgram, and Philip Zimbardo. Augustine Brannigan argues that the reliance of these psychologists on experimentation has led to questions around validity and replication of their studies. The author explores new research and archival work relating to these studies and outlines a new approach to experimentation that repudiates the use of deception in human experiments and provides clues to how social psychology can re-articulate its premises and future lines of research. Based on the author's 2004 work The Rise and Fall of Social Psychology, in which he critiques the experimental methods used, the book advocates for a return to qualitative methods to redeem the essential social dimensions of social psychology. Covering famous studies such as the Stanford Prison Experiment, Milgram's studies of obedience, Sherif's Robbers Cave, and Rosenhan's expose of psychiatric institutions, this is essential and fascinating reading for students of social psychology, and the social sciences. It's also of interest to academics and researchers interested in engaging with a critical approach to classical social psychology, with a view to changing the future of this important discipline.

This brilliant CGP book covers all the maths skills needed in AS and A-Level Psychology (the use of maths is required for up to 10% of the marks in the final exams and assessments). It explains Calculations, Graph Skills and Statistics, with clear study notes and step-by-step examples in the context of Psychology. And to make sure you've really got to grips with it all, there are practice questions for each topic - with answers included at the back of the book.

This book offers a refreshing new approach to mental health by showing how 'mental health' behaviours, lived experiences, and our interventions arise from our social worlds and not from our neurophysiology gone wrong. It is part of a trilogy which offers a new way of doing psychology focusing on people's social and societal environments as determining their behaviour, rather than internal and individualistic attributions. 'Mental health' behaviours are carefully analysed as ordinary behaviours which have become exaggerated and chronic because of the bad life situations people are forced to endure, especially as children. This shifts mental health treatments away from the dominance of psychology and psychiatry to show that social action is needed because many of these bad life situations are produced by our modern society itself. By providing new ways for readers to rethink everything they thought they knew about mental health issues and how to change them, Bernard Guerin also explores how by changing our environmental contexts (our local, societal, and discursive worlds), we can improve mental health interventions. This book reframes 'mental health' into a much wider social context to show how societal structures restrict our opportunities and pathways to produce bad life situations, and how we can also learn from those who manage to deal with the very same bad life situations through crime, bullying, exploitation, and dropping out of mainstream society, rather than through the 'mental health' behaviours. By merging psychology and psychiatry into the social sciences, Guerin seeks to better understand how humans operate in their social, cultural, economic, patriarchal, discursive, and societal worlds, rather than being isolated inside their heads with a 'faulty brain', and this will provide fascinating reading for academics and students in psychology and the social sciences, and for counsellors and therapists.

Comprehensive and accessible treatment of the common measurement models for the social, behavioral, and health sciences Explains the adequate use of measurement models for test construction, points out their merits and drawbacks, and critically discusses topics that have raised and continue to raise controversy. May be used in advanced courses on applied psychometrics and is attractive to both researchers and graduate students in psychology, education, sociology, political science, medicine and marketing, policy research, and opinion research

Delivering Psycho-educational Evaluation Results to Parents presents a concrete and adaptable Feedback Model that efficiently communicates complex evaluation results to parents in an easily understandable manner. The book discusses a model rooted in basic learning principles, effective communication practices, and practitioner empathy towards the parent experience of the home-school relationship, hinging upon practitioners and parents jointly creating a permanent product of the evaluation results during the feedback process. It provides early career school psychologists with a parent-friendly Feedback Model that can be adapted to their school-based setting. The text includes specific verbiage to explaining constructs in the cognitive, achievement, visual-motor, and social-emotional domains, along with considerations in application to working with diverse populations. The text is intended for school psychologists and professionals who complete psycho-educational evaluations for special education eligibility. More specifically, the text is envisioned to support the graduate training of school psychologists and the professional development of early career professionals in the field.

Delivering Psycho-educational Evaluation Results to Parents presents a concrete and adaptable Feedback Model that efficiently communicates complex evaluation results to parents in an easily understandable manner. The book discusses a model rooted in basic learning principles, effective communication practices, and practitioner empathy towards the parent experience of the home-school relationship, hinging upon practitioners and parents jointly creating a permanent product of the evaluation results during the feedback process. It provides early career school psychologists with a parent-friendly Feedback Model that can be adapted to their school-based setting. The text includes specific verbiage to explaining constructs in the cognitive, achievement, visual-motor, and social-emotional domains, along with considerations in application to working with diverse populations. The text is intended for school psychologists and professionals who complete psycho-educational evaluations for special education eligibility. More specifically, the text is envisioned to support the graduate training of school psychologists and the professional development of early career professionals in the field.

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It primarily focuses on regression modeling, classification and discrimination, dimension reduction, and clustering. The text thoroughly explains the concepts and derivations of the AIC, BIC, and related criteria and includes a wide range of practical examples of model selection and evaluation criteria. To estimate and evaluate models with a large number of predictor variables, the author presents regularization methods, including the L1 norm regularization that gives simultaneous model estimation and variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for researchers and practitioners in industrial and systems engineering, information science, life science, and other areas.

Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Highlights of the new edition include: More learning tools to strengthen readers' understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude towards Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book's accessible introduction.

* Explores the overlap/parallels between the work of clinicians and qualitative researchers. * Suggests how postmodern therapeutic approaches can be integrated into methods of data collection and analysis. * Examines a range of postmodern therapies, including collaborative language systems, narrative therapy, and solution-focused brief therapy. * Offers an innovative and unique way of enhancing the skills of the qualitative researcher, with an emphasis on reflective practice.

There is a recent surge in the use of randomized controlled trials (RCTs) within education globally, with disproportionate claims being made about what they show, 'what works', and what constitutes the best 'evidence'. Drawing on up-to-date scholarship from across the world, Taming Randomized Controlled Trials in Education critically addresses the increased use of RCTs in education, exploring their benefits, limits and cautions, and ultimately questioning the prominence given to them. While acknowledging that randomized controlled trials do have some place in education, the book nevertheless argues that this place should be limited. Drawing together all arguments for and against RCTs in a comprehensive and easily accessible single volume, the book also adds new perspectives and insights to the conversation; crucially, the book considers the limits of their usefulness and applicability in education, raising a range of largely unexplored concerns about their use. Chapters include discussions on: The impact of complexity theory and chaos theory. Design issues and sampling in randomized controlled trials. Learning from clinical trials. Data analysis in randomized controlled trials. Reporting, evaluating and generalizing from randomized controlled trials. Considering key issues in understanding and interrogating research evidence, this book is ideal reading for all students on Research Methods modules, as well as those interested in undertaking and reviewing research in the field of education.

* Explores the overlap/parallels between the work of clinicians and qualitative researchers. * Suggests how postmodern therapeutic approaches can be integrated into methods of data collection and analysis. * Examines a range of postmodern therapies, including collaborative language systems, narrative therapy, and solution-focused brief therapy. * Offers an innovative and unique way of enhancing the skills of the qualitative researcher, with an emphasis on reflective practice.

Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting. The frameworks draw on recent advances in statistical methodology to provide new tools for tackling challenges such as disaggregation, measurement error, missing data, and combining multiple data sources. The methods apply to single demographic series, or to entire demographic systems. The methods unify estimation and forecasting, and yield detailed measures of uncertainty. The book assumes minimal knowledge of statistics, and no previous knowledge of demography. The authors have developed a set of R packages implementing the methods. Data and code for all applications in the book are available on www.bdef-book.com. "This book will be welcome for the scientific community of forecasters...as it presents a new approach which has already given important results and which, in my opinion, will increase its importance in the future." ~Daniel Courgeau, Institut national d'etudes demographiques

Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. The book provides you with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Drawing on his extensive work as a statistician and professor at Cardiff University School of Medicine, the author brings together methods for calculating confidence intervals for proportions and several other important measures, including differences, ratios, and nonparametric effect size measures generalizing Mann-Whitney and Wilcoxon tests. He also explains three important approaches to obtaining intervals for related measures. Many examples illustrate the application of the methods in the health and social sciences. Requiring little computational skills, the book offers user-friendly Excel spreadsheets for download at www.crcpress.com, enabling you to easily apply the methods to your own empirical data.

Measures of Interobserver Agreement and Reliability, Second Edition covers important issues related to the design and analysis of reliability and agreement studies. It examines factors affecting the degree of measurement errors in reliability generalization studies and characteristics influencing the process of diagnosing each subject in a reliability study. The book also illustrates the importance of blinding and random selection of subjects. New to the Second Edition New chapter that describes various models for methods comparison studies New chapter on the analysis of reproducibility using the within-subjects coefficient of variation Emphasis on the definition of the subjects' and raters' population as well as sample size determination This edition continues to offer guidance on how to run sound reliability and agreement studies in clinical settings and other types of investigations. The author explores two ways of producing one pooled estimate of agreement from several centers: a fixed-effect approach and a random sample of centers using a simple meta-analytic approach. The text includes end-of-chapter exercises as well as downloadable resources of data sets and SAS code.

This is an essential how-to guide on the application of structural equation modeling (SEM) techniques with the AMOS software, focusing on the practical applications of both simple and advanced topics. Written in an easy-to-understand conversational style, the book covers everything from data collection and screening to confirmatory factor analysis, structural model analysis, mediation, moderation, and more advanced topics such as mixture modeling, censored date, and non-recursive models. Through step-by-step instructions, screen shots, and suggested guidelines for reporting, Collier cuts through abstract definitional perspectives to give insight on how to actually run analysis. Unlike other SEM books, the examples used will often start in SPSS and then transition to AMOS so that the reader can have full confidence in running the analysis from beginning to end. Best practices are also included on topics like how to determine if your SEM model is formative or reflective, making it not just an explanation of SEM topics, but a guide for researchers on how to develop a strong methodology while studying their respective phenomenon of interest. With a focus on practical applications of both basic and advanced topics, and with detailed work-through examples throughout, this book is ideal for experienced researchers and beginners across the behavioral and social sciences.

Survey Development: A Theory-Driven Mixed Methods Approach provides both an overview of standard methods and tools for developing and validating surveys and a conceptual basis for survey development. It advocates logical reasoning that combines theory related to construct validity with theory regarding design, and theory regarding survey response, item review, and identification of misfitting responses. The book has 14 chapters which are divided into four parts. Part A includes six chapters that deal with theory and methodology. Part B has five chapters and it gets into the process of constructing the survey. Part C comprises two chapters devoted to assessing the quality or psychometric properties (reliability and validity) of survey responses. Finally, the one chapter in Part D is an attempt to present a synopsis of what was covered in the previous chapters in regard to developing a survey with the Theory-Driven-Mixed-Methods (TDMM) framework for developing survey and conducting survey research. This provides a full process for survey development intended to yield results that can support validity. A mixed methods approach integrates both qualitative and quantitative data outcomes. Including detailed online resources, this book is suitable for graduate students who use or are responsible for interpretation of survey research and survey data as well as survey methodologists and practitioners who use surveys in their field.

Psychoeducational Assessment of Preschool Children, Fifth Edition, provides academics and school-based practitioners such as psychologists, speech-language pathologists, and social workers with an up-to-date guide to the assessment of young children. Long recognized as the standard text and reference in its field, this comprehensive, skill-building overview is organized into four sections: foundations, ecological assessment, assessment of developmental domains, and special considerations. Chapters written by recognized scholars in the field cover theory, research, and application. This thoroughly revised new edition addresses current developments in preschool assessment, new policies and legislation, and student/family population demographics.

The number of innovative applications of randomization tests in various fields and recent developments in experimental design, significance testing, computing facilities, and randomization test algorithms have necessitated a new edition of Randomization Tests. Updated, reorganized, and revised, the text emphasizes the irrelevance and implausibility of the random sampling assumption for the typical experiment in three completely rewritten chapters. It also discusses factorial designs and interactions and combines repeated-measures and randomized block designs in one chapter. The authors focus more attention on the practicality of N-of-1 randomization tests and the availability of user-friendly software to perform them. In addition, they provide an overview of free and commercial computer programs for all of the tests presented in the book. Building on the previous editions that have served as standard textbooks for more than twenty-five years, Randomization Tests, Fourth Edition includes downloadable resources of up-to-date randomization test programs that facilitate application of the tests to experimental data. This CD-ROM enables students to work out problems that have been added to the chapters and helps professors teach the basics of randomization tests and devise tasks for assignments and examinations.

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.