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There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.
Qualitative research --- Mixed methods research. --- Social sciences --- Methodology. --- Research --- Mathematical models.
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There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.
Qualitative research --- Mixed methods research. --- Social sciences --- Methodology. --- Research --- Mathematical models.
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"This book is a proposed supplementary text that guides social scientists and their students to fully characterize and assess the properties of research designs before they implement them. The book leads readers to answer questions like: - What questions is my study honestly well-equipped to answer? - How do I choose between gathering less data on more units versus more data on fewer units? - If I'm right, how likely is it that my study will change the mind of a committed skeptic? - How sensitive are my findings to my assumptions? These questions are surprisingly tricky to answer even for the most seasoned researchers. A major part of the trouble is that most scholars lack a definition of what constitutes a complete research design. The book will help researchers and students to decide on a method of assessment and then to measure the strength of that research design. The book applies this framework for common social science research designs. The book has four parts: (1) an introduction to the general framework to conceptualize design; (2) a design library of standard design types for researchers to draw from; (3) a set of research principles to guide readers with data gathering, question formation, and analysis; and (4) an extension of the broader use of the approach and framework for researchers, critiques and peer reviewers, and also for research funders. Each chapter is anchored by a narrative theoretical section that are enhanced by interactive R modules to illustrate design tradeoffs. In addition, each chapter includes a "lab," demonstrating how to implement and learn about each design; and exercises that extend the lab using interactive assessment tools. The book can be used independently as a supplemental course book for graduate and advanced graduate students, but is also supported by an online set of R repositories that could be used in conjunction with the book, as well as a piece of web software that allows researchers to assess designs without using the statistical packages"-- "A state-of-the-art approach to evaluating research design for students and scholars across the social sciencesAssessing the properties of research designs before implementing them can be tricky for even the most seasoned researchers. This book provides a powerful framework-Model, Inquiry, Data Strategy, and Answer Strategy, or MIDA-for describing any empirical research design in the social sciences. MIDA enables you to characterize the key analytic features of observational and experimental designs, qualitative and quantitative designs, and descriptive and causal designs. An accompanying algorithm lets you declare designs in the MIDA framework, diagnose properties such as bias and precision, and redesign features like sampling, assignment, measurement, and estimation procedures. Research Design in the Social Sciences is an essential tool kit for the entire life of a research project, from planning and realization of design to the integration of your results into the scientific literature.A must-have resource for current and future researchers who want to learn about the properties of their designs before they implement themIncludes a library of the most common designs in the social sciencesProvides a complete declaration of the canonical design for each library entry, describes the circumstances under which the design can be strong or weak, and explores the consequences of the choices under the research designer's controlAccompanied by online resources that can be used in conjunction with the bookAn ideal textbook for graduate students and advanced undergraduates"--
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Throughout the world, voters lack access to information about politicians, government performance, and public services. Efforts to remedy these informational deficits are numerous. Yet do informational campaigns influence voter behavior and increase democratic accountability? Through the first project of the Metaketa Initiative, sponsored by the Evidence in Governance and Politics (EGAP) research network, this book aims to address this substantive question and at the same time introduce a new model for cumulative learning that increases coordination among otherwise independent researcher teams. It presents the overall results (using meta-analysis) from six independently conducted but coordinated field experimental studies, the results from each individual study, and the findings from a related evaluation of whether practitioners utilize this information as expected. It also discusses lessons learned from EGAP's efforts to coordinate field experiments, increase replication of theoretically important studies across contexts, and increase the external validity of field experimental research.
Government accountability --- Government information --- Voting research --- Voting --- Voting behavior research --- Elections --- Information, Government --- Freedom of information --- Public records --- Accountability in government --- Public administration --- Responsibility --- Research --- Developing countries --- Emerging nations --- Fourth World --- Global South --- LDC's --- Least developed countries --- Less developed countries --- Newly industrialized countries --- Newly industrializing countries --- NICs (Newly industrialized countries) --- Third World --- Underdeveloped areas --- Underdeveloped countries --- Politics and government --- Research.
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