To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.
Every country, every subnational government, and every district has a designated population, and this has a bearing on politics in ways most citizens and policymakers are barely aware of. Population and Politics provides a comprehensive evaluation of the political implications stemming from the size of a political unit – on social cohesion, the number of representatives, overall representativeness, particularism ('pork'), citizen engagement and participation, political trust, electoral contestation, leadership succession, professionalism in government, power concentration in the central apparatus of the state, government intervention, civil conflict, and overall political power. A multimethod approach combines field research in small states and islands with cross-country and within-country data analysis. Population and Politics will be of interest to academics, policymakers, and anyone concerned with decentralization and multilevel governance.
An SPSS Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of SPSS using real political science data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using SPSS. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of SPSS step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in SPSS to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.
Whilst a great deal of progress has been made in recent decades, concerns persist about the course of the social sciences. Progress in these disciplines is hard to assess and core scientific goals such as discovery, transparency, reproducibility, and cumulation remain frustratingly out of reach. Despite having technical acumen and an array tools at their disposal, today's social scientists may be only slightly better equipped to vanquish error and construct an edifice of truth than their forbears – who conducted analyses with slide rules and wrote up results with typewriters. This volume considers the challenges facing the social sciences, as well as possible solutions. In doing so, we adopt a systemic view of the subject matter. What are the rules and norms governing behavior in the social sciences? What kinds of research, and which sorts of researcher, succeed and fail under the current system? In what ways does this incentive structure serve, or subvert, the goal of scientific progress?
In 2016, 90% of young Americans reported an interest in politics. 80% intended to vote. Yet only 43% of people between the ages of 18 and 29 ended up actually casting a ballot. Making Young Voters investigates what lies at the core of this gap. The authors' in-depth, interdisciplinary approach reveals that political apathy is not the reason for low levels of youth turnout. Rather, young people too often fail to follow through on their political interests and intentions. Those with 'noncognitive' skills related to self-regulation are more likely to overcome internal and external barriers to participation. This book combines theory from psychology, economics, child development, and more to explore possible solutions rooted in civic education and electoral reform. This potentially paradigm-shifting contribution to the literature of American politics serves to influence not only our understanding of voter turnout, but also the fundamental connections between the education system, electoral institutions, and individual civic behavior in a democracy. How young people vote affects not only each individual future, but that of the United States, and of us all.
Is it possible to compare French presidential politics with village leadership in rural India? Most social scientists are united in thinking such unlikely juxtapositions are not feasible. Boswell, Corbett and Rhodes argue that they are possible. This book explains why and how. It is a call to arms for interpretivists to embrace creatively comparative work. As well as explaining, defending and illustrating the comparative interpretive approach, this book is also an engaging, hands-on guide to doing comparative interpretive research, with chapters covering design, fieldwork, analysis and writing. The advice in each revolves around 'rules of thumb', grounded in experience, and illustrated through stories and examples from the authors' research in different contexts around the world. Naturalist and humanist traditions have thus far dominated the field but this book presents a real alternative to these two orthodoxies which expands the horizons of comparative analysis in social science research.
A Stata Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of Stata using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using Stata. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of Stata step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in Stata to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.
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.
What is a focus group? Why do we use them? When should we use them? When should we not? Focus Groups for the Social Science Researcher provides a step-by-step guide to undertaking focus groups, whether as a stand-alone method or alongside other qualitative or quantitative methods. It recognizes the challenges that focus groups encounter and provides tips to address them. The book highlights three unique, inter-related characteristics of focus groups. First, they are inherently social in form. Second, the data emerge organically through conversation; they are emic in nature. Finally, focus groups generate data at three levels of analysis: the individual, group, and interactive level. The book builds from these three characteristics to explain when focus groups can usefully be employed in different research designs. This is an essential text for students and researchers looking for a concise and accessible introduction to this important approach to data collection.
Reflecting a sea change in how empirical research has been conducted over the past three decades, Foundations of Agnostic Statistics presents an innovative treatment of modern statistical theory for the social and health sciences. This book develops the fundamentals of what the authors call agnostic statistics, which considers what can be learned about the world without assuming that there exists a simple generative model that can be known to be true. Aronow and Miller provide the foundations for statistical inference for researchers unwilling to make assumptions beyond what they or their audience would find credible. Building from first principles, the book covers topics including estimation theory, regression, maximum likelihood, missing data, and causal inference. Using these principles, readers will be able to formally articulate their targets of inquiry, distinguish substantive assumptions from statistical assumptions, and ultimately engage in cutting-edge quantitative empirical research that contributes to human knowledge.
This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.
The third edition of the best-selling The Fundamentals of Political Science Research provides an introduction to the scientific study of politics. It offers the basic tools necessary for readers to become both critical consumers and beginning producers of scientific research on politics. The authors present an integrated approach to research design and empirical analyses whereby researchers can develop and test causal theories. They use examples from political science research that students will find interesting and inspiring, and that will help them understand key concepts. The book makes technical material accessible to students who might otherwise be intimidated by mathematical examples. This revised third edition features new 'Your Turn' boxes meant to engage students. The edition also has new sections added throughout the book to enhance the content's clarity and breadth of coverage.
Egocentric network analysis is used widely across the social sciences, especially in anthropology, political science, economics, and sociology, and is increasingly being employed in communications, informatics, and business and marketing studies. Egocentric network analysis requires a unique set of data collection and analysis skills that overlap only minimally with other network methodologies. However, until now there has been no single reference for conceptualizing, collecting, and analyzing egocentric social network data. This comprehensive guide to study design, data collection, and analysis brings together the state of knowledge with the most effective research tools to guide newcomers to this field. It is illustrated with many engaging examples and graphics and assumes no prior knowledge. Covering the entire research process in a logical sequence, from conceptualizing research questions to interpreting findings, this volume provides a solid foundation for researchers at any stage of their career to learn and apply ego network methods.
Mainstream international relations continues to assume that the world is governed by calculable risk based on estimates of power, despite repeatedly being surprised by unexpected change. This ground breaking work departs from existing definitions of power that focus on the actors' evolving ability to exercise control in situations of calculable risk. It introduces the concept of 'protean power', which focuses on the actors' agility as they adapt to situations of uncertainty. Protean Power uses twelve real world case studies to examine how the dynamics of protean and control power can be tracked in the relations among different state and non-state actors, operating in diverse sites, stretching from local to global, in both times of relative normalcy and moments of crisis. Katzenstein and Seybert argue for a new approach to international relations, where the inclusion of protean power in our analytical models helps in accounting for unforeseen changes in world politics.
Deadly Clerics explains why some Muslim clerics adopt the ideology of militant jihadism while most do not. The book explores multiple pathways of cleric radicalization and shows that the interplay of academic, religious, and political institutions has influenced the rise of modern jihadism through a mechanism of blocked ambition. As long as clerics' academic ambitions remain attainable, they are unlikely to espouse violent jihad. Clerics who are forced out of academia are more likely to turn to jihad for two reasons: jihadist ideas are attractive to those who see the system as turning against them, and preaching a jihad ideology can help these outsider clerics attract supporters and funds. The book draws on evidence from various sources, including large-scale statistical analysis of texts and network data obtained from the Internet, case studies of clerics' lives, and ethnographic participant observations at sites in Cairo, Egypt.
The Space between Us brings the connection between geography, psychology, and politics to life. By going into the neighborhoods of real cities, Enos shows how our perceptions of racial, ethnic, and religious groups are intuitively shaped by where these groups live and interact daily. Through the lens of numerous examples across the globe and drawing on a compelling combination of research techniques including field and laboratory experiments, big data analysis, and small-scale interactions, this timely book provides a new understanding of how geography shapes politics and how members of groups think about each other. Enos' analysis is punctuated with personal accounts from the field. His rigorous research unfolds in accessible writing that will appeal to specialists and non-specialists alike, illuminating the profound effects of social geography on how we relate to, think about, and politically interact across groups in the fabric of our daily lives.
Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
The uncertainty that researchers face in specifying their estimation model threatens the validity of their inferences. In regression analyses of observational data, the 'true model' remains unknown, and researchers face a choice between plausible alternative specifications. Robustness testing allows researchers to explore the stability of their main estimates to plausible variations in model specifications. This highly accessible book presents the logic of robustness testing, provides an operational definition of robustness that can be applied in all quantitative research, and introduces readers to diverse types of robustness tests. Focusing on each dimension of model uncertainty in separate chapters, the authors provide a systematic overview of existing tests and develop many new ones. Whether it be uncertainty about the population or sample, measurement, the set of explanatory variables and their functional form, causal or temporal heterogeneity, or effect dynamics or spatial dependence, this book provides guidance and offers tests that researchers from across the social sciences can employ in their own research.