A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate-and sometimes conflicting-ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.

A New Way of Analyzing Object Data from a Nonparametric Viewpoint Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds. It also presents in-depth applications to practical problems arising in a variety of fields, including statistics, medical imaging, computer vision, pattern recognition, and bioinformatics. The book begins with a survey of illustrative examples of object data before moving to a review of concepts from mathematical statistics, differential geometry, and topology. The authors next describe theory and methods for working on various manifolds, giving a historical perspective of concepts from mathematics and statistics. They then present problems from a wide variety of areas, including diffusion tensor imaging, similarity shape analysis, directional data analysis, and projective shape analysis for machine vision. The book concludes with a discussion of current related research and graduate-level teaching topics as well as considerations related to computational statistics. Researchers in diverse fields must combine statistical methodology with concepts from projective geometry, differential geometry, and topology to analyze data objects arising from non-Euclidean object spaces. An expert-driven guide to this approach, this book covers the general nonparametric theory for analyzing data on manifolds, methods for working with specific spaces, and extensive applications to practical research problems. These problems show how object data analysis opens a formidable door to the realm of big data analysis.

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Reciprocity Rules explores the rich and complicated relationships that develop between anthropologists and research participants over time. Focusing on compensation and the creation of friendship and "family" relationships, contributors discuss what, when, and how researchers and the people with whom they work give to each other in and beyond fieldwork. Through reflexivity and narrative, the contributors to this edited collection, who are in various stages in their professional careers and whose research spans three continents and eight countries, reflect on the ways in which they have compensated their research participants and given back to host communities, as well as the varied responses to their efforts. The contributors consider both material and non-material forms of reciprocity, stories of successes and failures, and the taken-for-granted notions of compensation, friendship, and "helping." In so doing, they address the interpersonal dynamics of power and agency in the field, examine cultural misunderstandings, and highlight the challenges that anthropologists face as they strive to maintain good relations with their hosts even when separated by time and space. The contributors argue that while learning, following, openly discussing, and writing about the local rules of reciprocity are always challenging, they are essential to responsible research practice and ongoing efforts to decolonize anthropology.

This book reconstructs the rise and fall of Wilhelm Wundt's fortunes, focusing for the first time on the role of Richard Avenarius as catalyst for the so-called "positivist repudiation of Wundt." Krauss specifically looks at the progressive disavowal of Wundtian ideas in the world of scientific psychology, and especially by his former pupils. This book provides important historical context and a critical discussion of the current state of research, in addition to a detailed consideration of Wundt's and Avenarius' systems of thought, as well as on their personal relationship. The author outlines the reception of Avenarius' conceptions among Wundt's pupils, such as Kulpe, Munsterberg and Titchener, and among other psychologists of the time, such as Ward, James and Ebbinghaus. Finally, this book presents Wundt's two-fold attempt to respond to the new trend through a criticism of the "materialistic" psychology, and a reformulation of his own ideas.

* 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

This book explains how to develop more effective risk communications using the Carnegie Mellon mental-model approach. Such communications are designed to contain, in readily usable form, the information that people need to make informed decisions about risks to health, safety, and the environment. The approach draws together methods from the natural and social sciences, providing a framework for interdisciplinary collaboration. It is demostrated with varied examples including electromagnetic fields, climate change, radon, and sexually transmitted diseases.

R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.

With recent advances in computing power and the widespread availability of preference, perception and choice data, such as public opinion surveys and legislative voting, the empirical estimation of spatial models using scaling and ideal point estimation methods has never been more accessible.The second edition of Analyzing Spatial Models of Choice and Judgment demonstrates how to estimate and interpret spatial models with a variety of methods using the open-source programming language R. Requiring only basic knowledge of R, the book enables social science researchers to apply the methods to their own data. Also suitable for experienced methodologists, it presents the latest methods for modeling the distances between points. The authors explain the basic theory behind empirical spatial models, then illustrate the estimation technique behind implementing each method, exploring the advantages and limitations while providing visualizations to understand the results. This second edition updates and expands the methods and software discussed in the first edition, including new coverage of methods for ordinal data and anchoring vignettes in surveys, as well as an entire chapter dedicated to Bayesian methods. The second edition is made easier to use by the inclusion of an R package, which provides all data and functions used in the book. David A. Armstrong II is Canada Research Chair in Political Methodology and Associate Professor of Political Science at Western University. His research interests include measurement, Democracy and state repressive action. Ryan Bakker is Reader in Comparative Politics at the University of Essex. His research interests include applied Bayesian modeling, measurement, Western European politics, and EU politics. Royce Carroll is Professor in Comparative Politics at the University of Essex. His research focuses on measurement of ideology and the comparative politics of legislatures and political parties. Christopher Hare is Assistant Professor in Political Science at the University of California, Davis. His research focuses on ideology and voting behavior in US politics, political polarization, and measurement. Keith T. Poole is Philip H. Alston Jr. Distinguished Professor of Political Science at the University of Georgia. His research interests include methodology, US political-economic history, economic growth and entrepreneurship. Howard Rosenthal is Professor of Politics at NYU and Roger Williams Straus Professor of Social Sciences, Emeritus, at Princeton. Rosenthal's research focuses on political economy, American politics and methodology.

Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem gives a number of perspectives from top methodologists and applied researchers on the best ways to attempt to answer Age-Period-Cohort related questions about society. Age-Period-Cohort (APC) analysis is a fundamental topic for any quantitative social scientist studying individuals over time. At the same time, it is also one of the most misunderstood and underestimated topics in quantitative methods. As such, this book is key reference material for researchers wanting to know how to deal with APC issues appropriately in their statistical modelling. It deals with the identification problem caused by the co-linearity of the three variables, considers why some currently used methods are problematic and suggests ideas for what applied researchers interested in APC analysis should do. Whilst the perspectives are varied, the book provides a unified view of the subject in a reader-friendly way that will be accessible to social scientists with a moderate level of quantitative understanding, across the social and health sciences.

Scientometrics for the Humanities and Social Sciences is the first ever book on scientometrics that deals with the historical development of both quantitative and qualitative data analysis in scientometric studies. It focuses on its applicability in new and emerging areas of inquiry. This important book presents the inherent potential for data mining and analysis of qualitative data in scientometrics. The author provides select cases of scientometric studies in the humanities and social sciences, explaining their research objectives, sources of data and methodologies. It illustrates how data can be gathered not only from prominent online databases and repositories, but also from journals that are not stored in these databases. With the support of specific examples, the book shows how data on demographic variables can be collected to supplement scientometric data. The book deals with a research methodology which has an increasing applicability not only to the study of science, but also to the study of the disciplines in the humanities and social sciences.

The Ozone Layer is an accessible history of stratospheric ozone, from its discovery in the nineteenth century to current investigations of the Antarctic ozone hole. Drawing directly on the scientific literature, Christie uses the story of ozone as a case study for examining fundamental issues relating to the practice of modern science and the conduct of scientific debate. Linking key debates in the philosophy of science to an example of real-world science it is an excellent and thought-provoking introduction to the philosophy of science.

People often try to figure out why they acted the way they did or why others close to them acted in a certain way. The thoughts we have about why things happened are known as attributions. People have these thoughts about communication behavior, and they communicate the thoughts that they have. This book brings together scholars from a variety of disciplines whose work focuses on the interplay of attribution processes and communication behavior in close relationships.

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 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 volume explores the abiding intellectual inertia in scientific psychology in relation to the discipline's engagement with problematic beliefs and assumptions underlying mainstream research practices, despite repeated critical analyses which reveal the weaknesses, and in some cases complete inappropriateness, of these methods. Such paradigmatic inertia is especially troublesome for a scholarly discipline claiming status as a science. The book offers penetrating analyses of many (albeit not all) of the most important areas where mainstream practices require either compelling justifications for their continuation or adjustments - possibly including abandonment - toward more apposite alternatives. Specific areas of concern addressed in this book include the systemic misinterpretation of statistical knowledge; the prevalence of a conception of measurement at odds with yet purporting to mimic the natural sciences; the continuing widespread reliance on null hypothesis testing; and the continuing resistance within psychology to the explicit incorporation of qualitative methods into its methodological toolbox. Broader level chapters examine mainstream psychology's systemic disregard for critical analysis of its tenets, and the epistemic and ethical problems this has created. This is a vital and engaging resource for researchers across psychology, and those in the wider behavioural and social sciences who have an interest in, or who use, psychological research methods.

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

1. The author is forefront of the application of IRT (classic and innovative methodologies). 2. Covers all IRT in broad brushstrokes in an accessible manner. 3. Includes an abundance of original and secondary sources to facilitate learning, including further reading, simulated datasets, and graphics.

1. The author is forefront of the application of IRT (classic and innovative methodologies). 2. Covers all IRT in broad brushstrokes in an accessible manner. 3. Includes an abundance of original and secondary sources to facilitate learning, including further reading, simulated datasets, and graphics.

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.

Contrasts are statistical procedures for asking focused questions of data. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis included here. But they, for the first time, will also be presented with a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates. By returning to these correlations throughout the book, the authors demonstrate special adaptations in a variety of contexts from two group comparison to one way analysis of variance contexts, to factorial designs, to repeated measures designs and to the case of multiple contrasts.

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.

Assessment of mental health, religion and culture: The development and examination of psychometric measures focuses on questionnaires that are of practical value for researchers interested in examining the relationship between the constructs of mental health, religion, and culture. Three particular areas of development and evaluation are represented within this volume: firstly, the psychometric properties of recently developed new questionnaires; secondly, the psychometric properties of established questionnaires that have been translated into other languages; and thirdly, the psychometric properties of questionnaires employed in various cultural contexts and religious samples. The research in this book is authored by a wide range of international scholars working on diverse samples and in a variety of different cultures. In doing so, the book facilitates future research in the area of mental health, religion, and culture. This book was originally published as two special issues of Mental Health, Religion & Culture.