This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563-588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.

Contemporary Studies in Sociology

1. Offers ready-to-play games of varying lengths and topics, giving teachers everything they need to implement active learning in the political science classroom. 2. Offers pedagogical data supporting classroom games and simulations, providing encouragement to professors and justification to administrators for active learning, 3. Serves as a primer for modifying and designing classroom games, supporting active professorial engagement and agency especially important in a time of online learning.

This book presents a series of analyses of educational policies - largely in the UK, but some also in Europe - researched by a team of social scientists who share a commitment to social justice and equity in education. We explore what social justice means, in educational policy and practice, and how it impacts on our understanding of both 'educational science' and 'the public good'. Using a social constructivist approach, the book argues that social justice requires a particular and critical analysis of the meaning of meritocracy, and of the way this term turns educational policies towards treating learning as a competition, in which many young people are constructed as 'losers'. We discuss how many terms in education are essentialised and have specific, and different, meanings for particular social groups, and how this may create issues in both quantitative survey methods and in determining what is 'the public good'. We discuss social justice across a range of intersecting social characteristics, including social class, ethnicity and gender, as they are applied across the educational policy spectrum, from early years to postgraduate education. We examine the ways that young people construct their identities, and the implications of this for understanding the 'public good' in educational practice. We consider the responsibilities of educational researchers to acknowledge these issues, and offer examples of researching with such a commitment. We conclude by considering how educational policy might contribute to a socially just, equitable and inclusive public good.

The competitiveness of firms, regions and countries greatly depends on the generation, dissemination and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and dissemination processes into the analysis so as to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central factors that are at odds with traditional modeling techniques anchored in equilibrium and homogeneity. This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co-operations and networks. In this context, knowledge is explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach supports applications in different domains ranging from sector-based research activities in knowledge-intensive industries to the activities of international research consortia engaged in basic and applied research. Following a general description of the SKIN model, several applications and modifications are presented. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results, while options for empirically validating the models' structure and outcomes are also discussed. The book considers the scope of further applications and outlines prospects for the development of joint modeling strategies.

This book seeks to introduce students to the challenges of 'real life' social research through a detailed consideration of eight recent empirical studies. Designed to complement existing introductory methods texts, it emphasises the importance of context in understanding and interpreting both the practice and 'product' of empirical research. The book focuses on research from eight key sub-areas of sociology, making it a useful secondary text for introductory courses on contemporary British society.

This book focuses on how important massive information is and how sensitive outcomes are to information. In this century humans now are coming up against the massive utilization of information in various contexts. The advent of super intelligence is drastically accelerating the evolution of the socio-economic system. Our traditional analytic approach must therefore be radically reformed in order to adapt to an information-sensitive framework, which means giving up myopic purification and the elimination of all considerations of massive information. In this book, authors who have shared and exchanged their ideas over the last 20 years, offer thorough examinations of the theoretical-ontological basis of complex economic interaction, econophysics, and agent-based modeling during the last several decades. This book thus provides the indispensable philosophical-scientific foundations for this new approach, and then moves on to empirical-epistemological studies concerning changes in sentiments and other movements in financial markets.

This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis depends in an integrated fashion on sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. The unifying theme is that supervised learning properly can be seen as a form of regression analysis. Key concepts and procedures are illustrated with a large number of real applications and their associated code in R, with an eye toward practical implications. The growing integration of computer science and statistics is well represented including the occasional, but salient, tensions that result. Throughout, there are links to the big picture. The third edition considers significant advances in recent years, among which are: the development of overarching, conceptual frameworks for statistical learning; the impact of "big data" on statistical learning; the nature and consequences of post-model selection statistical inference; deep learning in various forms; the special challenges to statistical inference posed by statistical learning; the fundamental connections between data collection and data analysis; interdisciplinary ethical and political issues surrounding the application of algorithmic methods in a wide variety of fields, each linked to concerns about transparency, fairness, and accuracy. This edition features new sections on accuracy, transparency, and fairness, as well as a new chapter on deep learning. Precursors to deep learning get an expanded treatment. The connections between fitting and forecasting are considered in greater depth. Discussion of the estimation targets for algorithmic methods is revised and expanded throughout to reflect the latest research. Resampling procedures are emphasized. The material is written for upper undergraduate and graduate students in the social, psychological and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems.

During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g., Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a, b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo retical and empirical aspects of behavioral research."

Investigates theoretically and empirically what it means to design technological artefacts while embracing the large number of practices which practitioners engage with when handling technologies. The authors discusses the fields of design and sociomateriality through their shared interests towards the basic nature of work, collaboration, organization, technology, and human agency, striving to make the debates and concepts originating in each field accessible to each other, and thus moving sociomateriality closer to the practical concerns of design and providing a useful analytical toolbox to information system designers and field researchers alike. Sociomaterial-Design: Bounding Technologies in Practice takes on the challenge of redefining design practices through insights from the emerging debate on sociomateriality. It does so by bringing forward a comparative examination of two longitudinal ethnographic studies of the practices within two emergency departments - one in Canada and one in the United States of America. A particular focus is placed upon the use of current collaborative artefacts within the emergency departments and the transformation into digital artefacts through design.

Advances in Autoethnography and Narrative Inquiry pays homage to two prominent scholars, Arthur Bochner and Carolyn Ellis, for their formative and formidable contributions to autoethnography, personal narrative, and alternative forms of scholarship. Their autoethnographic-and life-project gives us tools for understanding shared humanity and precious diversity; for striving to become ever-more empathic, loving, and ethical; and for living our best creative, relational, and public lives. The collection is organized into two sections: "Foundations" and "Futures." Contributors to "Foundations" explore Carolyn and Art's scholarship and legacy and/or their singular presence in the author's life. Contributors to "Futures" offer novel and innovative applications of autoethnographic and narrative inquiry. Throughout, contributors demonstrate how Bochner's and Ellis' work has created and shifted the terrain of autoethnographic and narrative research. This collection will be of interest to researchers familiar with Bochner's and Ellis' research. It also serves as a resource for graduate students, scholars, and professionals who have an interest in autoethnographic and narrative research. This collection can be used in upper-division undergraduate courses and graduate courses solely about autoethnography and narrative, and as a secondary text for courses about ethnography and qualitative research.

Uniting methods from disciplines across the social sciences and humanities, this hands-on guide develops a novel approach to doing document analysis. The authors present a framework for studying documents that enables you to conduct a rich and systematic analysis of documents in all their diversity. Focussing on document analysis both in practice and as practice, the book provides you with an innovative and versatile toolkit for analysing print and digital documents. It also: Highlights the impacts of digitalisation on documents themselves and the methods used to study them Has a strong focus on research ethics and critical engagement with digital sources Offers practical guidance on preparing and doing a document analysis research project. The book offers insightful perspectives both on the indispensable role of documents in our society and practical advice on how you can best analyse documents and their significance.

"Social Simulation for a Digital Society" provides a cross-section of state-of-the-art research in social simulation and computational social science. With the availability of big data and faster computing power, the social sciences are undergoing a tremendous transformation. Research in computational social sciences has received considerable attention in the last few years, with advances in a wide range of methodologies and applications. Areas of application of computational methods range from the study of opinion and information dynamics in social networks, the formal modeling of resource use, the study of social conflict and cooperation to the development of cognitive models for social simulation and many more. This volume is based on the Social Simulation Conference of 2017 in Dublin and includes applications from across the social sciences, providing the reader with a demonstration of the highly versatile research in social simulation, with a particular focus on public policy relevance in a digital society. Chapters in the book include contributions to the methodology of simulation-based research, theoretical and philosophical considerations, as well as applied work. This book will appeal to students and researchers in the field.

Advanced Statistics provides a rigorous development of statistics that emphasizes the definition and study of numerical measures that describe population variables. Volume 1 studies properties of commonly used descriptive measures. Volume 2 considers use of sampling from populations to draw inferences concerning properties of populations. The volumes are intended for use by graduate students in statistics and professional statisticians, although no specific prior knowledge of statistics is assumed. The rigorous treatment of statistical concepts requires that the reader be familiar with mathematical analysis and linear algebra, so that open sets, continuous functions, differentials, Raman integrals, matrices, and vectors are familiar terms.

This book presents the proceedings from ECONOPHYS-2015, an international workshop held in New Delhi, India, on the interrelated fields of "econophysics" and "sociophysics", which have emerged from the application of statistical physics to economics and sociology. Leading researchers from varied communities, including economists, sociologists, financial analysts, mathematicians, physicists, statisticians, and others, report on their recent work, discuss topical issues, and review the relevant contemporary literature. A society can be described as a group of people who inhabit the same geographical or social territory and are mutually involved through their shared participation in different aspects of life. It is possible to observe and characterize average behaviors of members of a society, an example being voting behavior. Moreover, the dynamic nature of interaction within any economic sector comprising numerous cooperatively interacting agents has many features in common with the interacting systems of statistical physics. It is on these bases that interest has grown in the application within sociology and economics of the tools of statistical mechanics. This book will be of value for all with an interest in this flourishing field.

"Jarvis does a real service by introducing a new vision of research into the current debates over the nature and mission of the academy."
--Continuing Higher Education Review

"Jarvis has managed to bridge the worlds of theory and professional practice in a way that will help each better understand the other."
--Jon Wergin, professor of educational studies, School of Education, Virginia Commonwealth University

Genuine understanding of any field can only be developed through practice in that field. Peter Jarvis, an internationally known authority in the field of professional adult and continuing education, shows how theories of practice evolve from the practice itself and are unique to each practitioner. Doing professional work gives practitioners many opportunities to question, test, and revise theories taught in graduate programs. Such practice-based research gives rise to personalized theories of practice and also raises new questions for personal exploration.

Using examples and vignettes drawn from professional fields and settings around the world, Jarvis provides valuable insights into the nature of professional practice, the ways professionals learn, and how education for practice can be enhanced at both the undergraduate and graduate levels. Jarvis examines why so many practitioners find their professional education inadequate preparation for actual practice, and he calls for a partnership between higher education and the professional workplace that will meet the challenges of the relationship between the two.

The Practitioner-Researcher is designed to help all practitioners for whom research is a tool in improving practice--from graduate students and their professors to employees in diverse industries or professional groups--and to facilitate an understanding of the relationship between practice and theory within the worlds of work and learning.

Multiple sclerosis is an incurable neurological disease of unknown cause with a fearful reputation for generating disability, unemployment, poverty and early death. This book critically surveys the current state of multiple sclerosis research, demonstrating the shortfall of current research undertaken on the lives of people with multiple sclerosis.

This collection sets a new agenda for conducting research on the EU and learns from past mistakes. In doing so it provides a state-of-the-art examination of social science research designs in EU studies while providing innovative guidelines for the advancement of more inclusive and empirically sensitive research designs in EU studies

This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics. Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.

A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences

"Statistics in the Social Sciences: Current Methodological Developments" presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Winemiller Conference: Methodological Developments of Statistics in the Social Sciences, an international meeting that focused on fostering collaboration among mathematical statisticians and social science researchers.

The book provides an accessible and insightful look at modern approaches to identifying and describing current, effective methodologies that ultimately add value to various fields of social science research. With contributions from leading international experts on the topic, the book features in-depth coverage of modern quantitative social sciences topics, including:

Correlation Structures

Structural Equation Models and Recent Extensions

Order-Constrained Proximity Matrix Representations

Multi-objective and Multi-dimensional Scaling

Differences in Bayesian and Non-Bayesian Inference

Bootstrap Test of Shape Invariance across Distributions

Statistical Software for the Social Sciences

"Statistics in the Social Sciences: Current Methodological Developments" is an excellent supplement for graduate courses on social science statistics in both statistics departments and quantitative social sciences programs. It is also a valuable reference for researchers and practitioners in the fields of psychology, sociology, economics, and market research.

Increasingly, social researchers are engaging with marginalized communities and becoming aware of their obligations to those they research. This book identifies issues associated with researching in what have traditionally been recognised as "hard to reach" communities and offers both conceptual analyses and practical suggestions on undertaking research that emphasizes the experience and contribution of those with whom the research is undertaken.

This book examines some of the major and most commonly used methods and statistics necessary for social science research. It is meant primarily for the beginners, and hence does not require any prior training in research methodology or statistics. The methods discussed include aggregate data analysis, the method of survey research, experimental and quasi-experimental research designs, participant observation, content analysis, and focus groups study. In a separate chapter the issue of quantitative and qualitative research methods and their uses has been discussed. An attempt has been made to assess these methods especially from the point of view of their adoption and application by social scientists working in the developing economies. Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan)

This volume covers such topics as psychological ownership in organizations, employee perceptions of fairness when human resource systems change, a culture-based perspective of organization development implementation, and mapping the progress of change through organizational levels.

This series examines the interrelations of politics and society, bringing together articles from an international and interdisciplinary community of scholars.