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."

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.

Agent-based modeling is a new technique for understanding how the dynamics of biological, social, and other complex systems arise from the characteristics and behaviors of the agents making up these systems. This innovative textbook gives students and scientists the skills to design, implement, and analyze agent-based models. It starts with the fundamentals of modeling and provides an introduction to NetLogo, an easy-to-use, free, and powerful software platform. Nine chapters then each introduce an important modeling concept and show how to implement it using NetLogo. The book goes on to present strategies for finding the right level of model complexity and developing theory for agent behavior, and for analyzing and learning from models. Agent-Based and Individual-Based Modeling features concise and accessible text, numerous examples, and exercises using small but scientific models. The emphasis throughout is on analysis--such as software testing, theory development, robustness analysis, and understanding full models--and on design issues like optimizing model structure and finding good parameter values. * The first hands-on introduction to agent-based modeling, from conceptual design to computer implementation to parameterization and analysis* Provides an introduction to NetLogo with nine chapters introducing an important modeling concept and showing how to implement it using NetLogo * Filled with examples and exercises, with updates and supplementary materials at http://www.railsback-grimm-abm-book.com/ * Designed for students and researchers across the biological and social sciences * Written by leading practitioners Leading universities that have adopted this book include: * Amherst College * Brigham Young University * Carnegie Mellon University* Cornell University * Miami University * Northwestern University * Old Dominion University * Portland State University * Rhodes College * Susquehanna University * University College, Dublin * University of Arizona* University of British Columbia* University of Michigan * University of South Florida* University of Texas at Austin * University of Virginia

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.

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.

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 book examines science fiction's theoretical and ontological backgrounds and how science fiction applies to the future of tourism. It recreates and invents the future of tourism in a creative and disruptive manner, reconceptualising tourism through alternative and quantum leap thinking that go beyond the normative or accepted view of tourism. The chapters, focusing on areas such as disruption, sustainability and technology, draw readers into the unknown future of tourism - a future that may be disruptive, dystopian or utopian. The book brings a new theoretical paradigm to the study of tourism in a post COVID-19 world and can be used to explore, frame and even form the future of tourism. It will capture the imagination and inspire readers to address tourism's challenges of tomorrow.

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 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.

Are you planning a desk-based qualitative research project, but aren't sure how to get started? This essential book provides all the guidance and advice you'll need to complete your project. Using two key visual pedagogical tools, the Metaphorical Tent and the Research Triangle, the book shows you how to produce vibrant and stimulating in-depth qualitative research that draws on high-quality data readily available via the internet. The book * takes you through the research process step-by-step, from choosing a topic to writing up conclusions; * examines a wide range of written, visual and audio data sources; * includes helpful case studies to demonstrate the practical application of concepts. Concise, practical and jam-packed with valuable tips, features and examples, this book will enable you to complete a successful desk-based research project you can be proud of.

Bernan Press proudly presents the sixteenth edition of Employment, Hours, and Earnings: States and Areas, 2022. A special addition to Bernan Press Handbook of U.S. Labor Statistics: Employment, Earnings, Prices, Productivity, and Other Labor Data, this reference is a consolidated wealth of employment information, providing monthly and annual data on hours worked and earnings made by industry, including figures and summary information spanning several years. These data are presented for states and metropolitan statistical areas. This edition features: Nearly 300 tables with data on employment for each state, the District of Columbia, and the nation's seventy-five largest metropolitan statistical areas (MSAs) Detailed, non-seasonally adjusted, industry data organized by month and year Hours and earnings data for each state, by industry An introduction for each state and the District of Columbia that denotes salient data and noteworthy trends, including changes in population and the civilian labor force, industry increases and declines, employment and unemployment statistics, and a chart detailing employment percentages, by industry Ranking of the seventy-five largest MSAs, including census population estimates, unemployment rates, and the percent change in total nonfarm employment, Concise technical notes that explain pertinent facts about the data, including sources, definitions, and significant changes; and provides references for further guidance A comprehensive appendix that details the geographical components of the seventy-five largest MSAs The employment, hours, and earnings data in this publication provide a detailed and timely picture of the fifty states, the District of Columbia, and the nation's seventy-five largest MSAs. These data can be used to analyze key factors affecting state and local economies and to compare national cyclical trends to local-level economic activity. This reference is an excellent source of information for analysts in both the public and private sectors. Readers who are involved in public policy can use these data to determine the health of the economy, to clearly identify which sectors are growing and which are declining, and to determine the need for federal assistance. State and local jurisdictions can use the data to determine the need for services, including training and unemployment assistance, and for planning and budgetary purposes. In addition, the data can be used to forecast tax revenue. In private industry, the data can be used by business owners to compare their business to the economy as a whole; and to identify suitable areas when making decisions about plant locations, wholesale and retail trade outlets, and for locating a particular sector base.

"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.

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.

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.

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.

"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.

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 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.

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.

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

Insights developed in the past two decades by philosophers of the social sciences can serve to enrich the challenging intellectual tasks of conceptualizing, investigating, and representing the human past. Likewise, intimate engagement with the writings of historians can deepen philosophers' understanding of the task of knowing the past. This volume brings these perspectives together and considers fundamental questions, such as: What is historical causation? What is a large historical structure? How can we best conceptualize "mentalities" and "identities"? What is involved in understanding the subjectivity of historical actors? What is involved in arriving at an economic history of a large region? How are actions and outcomes related? The arguments touch upon a wide range of historical topics -- the Chinese and French Revolutions, the extension of railroads in the nineteenth century, and the development of agriculture in medieval China.