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Sample design is key to all surveys, fundamental to data collection, and to the analysis and interpretation of the data.…
Introduction to Survey Sampling, Second Edition provides an authoritative and accessible source on sample design strategies and procedures that is a required reading for anyone collecting or analyzing survey data. Graham Kalton discusses different types of probability samples, stratification (pre and post), clustering, dual frames, replicates, response, base weights, design effects, and effective sample size. It is a thorough revision and update of the first edition, published more than 35 years ago. Although the concepts of probability sampling are largely the same, there have been important developments in the application of these concepts as research questions have increasingly spanned multiple disciplines, computers have become central to data collection as well as data analysis, and cell phones have become ubiquitous, but response rates have fallen, and public willingness to engage in survey research has waned. While most of the volume focuses on probability samples, there is also a chapter on nonprobability samples, which are becoming increasingly important with the rise of social media and the world wide web.
Elementary Regression Modeling builds on simple differences between groups to explain regression and regression modeling. User-friendly and immediately accessible, this…
book gives readers a thorough understanding of control modeling, interaction modeling, modeling linearity with spline variables, and creating research hypotheses that serve as a conceptual basis for many of the processes and procedures quantitative researchers follow when conducting regression analyses.
This practical book uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing…
propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated…
their implementation coincided with major changes in the research interests of, and data availability for, social scientists. Specifically, the last two decades have seen an increase in the availability of panel data sets, other hierarchically structured data sets including spatially organized data, along with interests in life course processes and the influence of context on individual behavior and outcomes. The Bayesian approach to statistics is well-suited for these types of data and research questions. Applied Bayesian Statistics is an introduction to these methods that is geared toward social scientists. Author Scott M. Lynch makes the material accessible by emphasizing application more than theory, explaining the math in a step-by-step fashion, and demonstrating the Bayesian approach in analyses of U.S. political trends drawing on data from the General Social Survey.
This accessible guide walks readers through the process of completing a social science research project. Written specifically to meet the…
needs of undergraduate research classes, it introduces students to a complete skill set, including: planning, design, analysis, argumentation, criticizing theories, building theories, modeling theories, choosing methods, gathering data, presenting evidence, and writing the final product. Students can use this text as a practical resource to navigate through each stage of the process, including choices between more advanced research techniques.
This Second Edition of The Tao of Statistics: A Path to Understanding (With No Math) provides a reader-friendly approach to…
statistics in plain English. Unlike other statistics books, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts as well as some of the most complex statistical models in use. The Second Edition adds coverage of big data to better address its impact on p-values and other key concepts; material on small data to show readers how to handle data with fewer data points than optimal; and other new topics like missing data and effect sizes. The book’s two characters (a high school principal and a director of public health) return in the revised edition, with their examples expanded and updated with reference to contemporary concerns in the fields of education and health.
This practical book uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing…
propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Focusing on research designs for projects that collect both qualitative and quantitative data, this practical book discusses strategies for bringing…
qualitative and quantitative methods together so that their combined strengths accomplish more than is possible with a single method. The approach is broadly interdisciplinary, reflecting the interest in mixed methods research of social scientists from anthropology, communication, criminal justice, education, evaluation, nursing, organizational behavior, psychology, political science, public administration, public health, sociology, social work, and urban studies. In contrast to an "anything goes" approach or a naïve hope that "two methods are better than one," the author argues that projects using mixed methods must pay even more attention to research design than single method approaches. The book’s practical emphasis on mixed methods makes it useful both to active researchers and to students who intend to pursue such a career.
Using a conceptual, non-mathematical approach, the updated Third Edition provides full coverage of the wide range of multivariate topics that…
graduate students across the social and behavioral sciences encounter. Authors Lawrence S. Meyers, Glenn Gamst, and A. J. Guarino integrate innovative multicultural topics in examples throughout the book, which include both conceptual and practical coverage of: statistical techniques of data screening; multiple regression; multilevel modeling; exploratory factor analysis; discriminant analysis; structural equation modeling; structural equation modeling invariance; survival analysis; multidimensional scaling; and cluster analysis.
Test Development and Validation by Gary Skaggs summarizes the latest test theories, frameworks for test development and validation, and guidance…
for developing tests in straightforward language in one core text. Students looking for clear, concise explanations of measurement, validity, and test development within a real-world context and with numerous examples will find this book to be an excellent learning resource. Author Gary Skaggs takes years of experience teaching test development to graduate students across social and behavioral sciences and consulting on a wide variety of government and institutional research projects to offer students a thorough, jargon-free, and highly applied book to help propel their own research and careers. Part I of the book, The Big Picture, sets the stage for test development, placing it within the larger context and history of measurement, emphasizing measurement concepts and their evolution over time. Part II, Test Development, covers the technical details of instrument and test development in logical order. Validation, Part III, links the conceptual bases provided in Part I with the technical process provided in Part II to conclude the book. For those students wanting to go further, software suggestions are referenced in the technical chapters, while Further Reading sections offer the original sources for more details. Exercises and Activities at the end of each chapter provide students a variety of ways to apply their knowledge, from conceptual questions to brief project ideas to data analysis problems.
Introduction to Cognitive Ethnography and Systematic Field Work by G. Mark Schoepfle provides a guide to the fundamentals of cognitive ethnography…
for qualitative research. A focus of this technique is collecting data from flexible but rigorous interviews. These interviews are flexible because they are designed to be structured around the semantic knowledge being elicited from the speaker, not around some pre-conceived design that is based on the researcher’s background, and they are rigorous because the basic linguistic and semantic structures are shared among all cultures. Written by one of the founders of this technique, this text provides a wealth of concentrated knowledge developed over years to best suit this collaborative and participant-centric research process. Eight chapters show how intertwined data collection and analysis are in this method. The first chapter offers a brief history and overview of the cognitive ethnography. Chapter 2 covers planning a research project, from developing a research question to ethics and IRB requirements. The next two chapters cover interview background, techniques, and structures. Chapter 5 addresses analysis while Chapter 6 covers transcription and translation. Chapter 7 covers observation, while a final chapter address writing a report for both consultants and outside audiences.
David Knoke and Song Yang′s Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of…
social network analysis. The authors convey key material while at the same time minimizing technical complexities. The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade. The new edition reflects developments and changes in practice over the past decade. The authors also describe important recent developments in network analysis, especially in the fifth chapter. Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.
Now with a new companion website! Using IBM® SPSS® Statistics: An Interactive Hands-On Approach, Third Edition gives readers an accessible…
and comprehensive guide to walking through SPSS®, providing them with step-by-step knowledge for effectively analyzing their data. From entering data to working with existing databases, and working with the help menu through performing factor analysis, Using IBM® SPSS® Statistics covers every aspect of SPSS® from introductory through intermediate statistics. The book is divided into parts that focus on mastering SPSS® basics, dealing with univariate statistics and graphing, inferential statistics, relational statistics, and more. Written using IBM® SPSS® version 25 and 24, and compatible with the earlier releases, this book is one of the most comprehensive SPSS® guides available. Bundle Using IBM® SPSS® Statistics: An Interactive Hands-On Approach with SAGE IBM® SPSS® Statistics v24.0 Student Version and SAVE! – Bundle ISBN: 978-1-5443-5071-4
100 Questions (and Answers) About Action Research identifies and answers the essential questions on the process of systematically approaching your…
practice from an inquiry-oriented perspective, with a focus on improving that practice. This unique text offers progressive instructors an alternative to the research status quo and serves as a reference for readers to improve their practice as advocates for those they serve. The Question and Answer format makes this an ideal supplementary text for traditional research methods courses, and also a helpful guide for practitioners in education, social work, criminal justice, health, business, and other applied disciplines.
A practical, skill-based introduction to data analysis and literacy We are swimming in a world of data, and this handy…
guide will keep you afloat while you learn to make sense of it all. In Data Literacy: A User′s Guide, David Herzog, a journalist with a decade of experience using data analysis to transform information into captivating storytelling, introduces students and professionals to the fundamentals of data literacy, a key skill in today’s world. Assuming the reader has no advanced knowledge of data analysis or statistics, this book shows how to create insight from publicly-available data through exercises using simple Excel functions. Extensively illustrated, step-by-step instructions within a concise, yet comprehensive, reference will help readers identify, obtain, evaluate, clean, analyze and visualize data. A concluding chapter introduces more sophisticated data analysis methods and tools including database managers such as Microsoft Access and MySQL and standalone statistical programs such as SPSS, SAS and R.
The updated Third Edition of this innovative text shows the unity within the diversity of activities called social research to…
help students understand how all social researchers construct representations of social life using theories, systematic data collection, and careful examination of that data. The book tackles questions like "What is social research?", "How does it differ from journalism, documentary film-making, or laboratory research in the natural sciences?", and "What is the researcher′s obligation to those he or she is studying?" Updated throughout with new references and examples, this edition is designed to evoke challenging questions regarding the nature of representation and the ethical challenges facing social scientific researchers. The text moves beyond standard research challenges to push readers to see the complex relationships among ethics, ideas, evidence, and outcomes.
Carol A. Chapelle shows readers how to design validation research for tests of human capacities and performance. Any test that…
is used to make decisions about people or programs should have undergone extensive research to demonstrate that the scores are actually appropriate for their intended purpose. Argument-Based Validation in Testing and Assessment is intended to help close the gap between theory and practice, by introducing, explaining, and demonstrating how test developers can formulate the overall design for their validation research from an argument-based perspective.
Items with ordered response categories are common in survey research, such as when respondents are asked how much they agree…
with certain statements. But how large are the differences between categories of response, and how well do they distinguish between respondents? This volume is the first to introduce the evaluation of rating scales to an audience of survey researchers. Evaluating Rating Scale Functioning for Survey Research provides researchers with an overview of rating scale analysis along with practical guidance on how to conduct such analyses with their own survey data. Author Stefanie A. Wind presents three categories of methods: Rasch models; non-Rasch Item Response Theory (IRT) models; and non-parametric models, together with practical examples. Tutorials, datasets, and software code (R and Facets) to accompany the book are available on the book’s website.
David Knoke and Song Yang′s Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of…
social network analysis. The authors convey key material while at the same time minimizing technical complexities. The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade. The new edition reflects developments and changes in practice over the past decade. The authors also describe important recent developments in network analysis, especially in the fifth chapter. Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.
Evaluability assessment (EA) can lead to development of sound program theory, increased stakeholder involvement and empowerment, better understanding of program…
culture and context, enhanced collaboration and communication, process and findings use, and organizational learning and evaluation capacity building. This book provides an up-to-date treatment of EA, clarifies what it actually is and how it can be used, demonstrates EA as an approach to evaluative inquiry with multidisciplinary and global appeal, and identifies and describes the purposes and benefits to using EA. Using case examples contributed by EA practitioners, the text illustrates important features of EA use, and showcases how EA is used in a variety of disciplines and evaluation contexts. This text is appropriate as an instructional text for graduate level evaluation courses and training, and as a resource for evaluation practitioners, policymakers, funding agencies, and professional training.