Practices of comparing shape how we perceive, organize, and change the world. This volume outlines the program of a new research agenda that places comparative practices at the center of an interdisciplinary exploration.

Practices of comparing shape how we perceive, organize, and change the world. Supposedly innocent, practices of comparing play a decisive role in forming categories, boundaries, and hierarchies; but they can also give an impetus to question and change such structures. Like almost no other human practice, comparing pervades all social, political, economic, and cultural spheres. This volume outlines the program of a new research agenda that places comparative practices at the center of an interdisciplinary exploration. Its contributions combine case studies with overarching systematic considerations. They show what insights can be gained and which further questions arise when one makes a seemingly trivial practice - comparing - the subject of in-depth research.

Comparisons not only prove fundamental in the epistemological foundation of modernity (Foucault, Luhmann), but they fulfil a central function in social life and the production of art. Taking a cue from the Practice Turn in sociology, the contributors are investigating the role of comparative practices in the formation of eighteenth-century literature and culture. The book conceives of social practices of comparing as being entrenched in networks of circulation of bodies, artefacts, discourses, and ideas, and aims to investigate how such practices ordered and changed British literature and culture during the long eighteenth century.

This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Qualitative comparative methods – and specifically controlled qualitative comparisons – are central to the study of politics. They are not the only kind of comparison, though, that can help us better understand political processes and outcomes. Yet there are few guides for how to conduct non-controlled comparative research. This volume brings together chapters from more than a dozen leading methods scholars from across the discipline of political science, including positivist and interpretivist scholars, qualitative methodologists, mixed-methods researchers, ethnographers, historians, and statisticians. Their work revolutionizes qualitative research design by diversifying the repertoire of comparative methods available to students of politics, offering readers clear suggestions for what kinds of comparisons might be possible, why they are useful, and how to execute them. By systematically thinking through how we engage in qualitative comparisons and the kinds of insights those comparisons produce, these collected essays create new possibilities to advance what we know about politics.

Contact, Conquest and Colonization brings together international historians and literary studies scholars in order to explore the force of practices of comparing in shaping empires and colonial relations at different points in time and around the globe. Whenever there was cultural contact in the context of European colonization and empire-building, historical records teem with comparisons among those cultures. This edited volume focuses on what historical agents actually do when they compare, rather than on comparison as an analytic method. Its contributors are thus interested in the ‘doing of comparison’, and explore the force of these practices of comparing in shaping empires and (post-)colonial relations between the sixteenth and twentieth centuries. This book will appeal to students and scholars of global history, as well as those interested in cultural history and the history of colonialism.

A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. Comparing Groups: Randomization and Bootstrap Methods Using R emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and the use of statistical computing in an effort to guide readers through the integration of design, statistical methodology, and computation to answer specific research questions regarding group differences. Utilizing the widely-used, freely accessible R software, the authors introduce a modern approach to promote methods that provide a more complete understanding of statistical concepts. Following an introduction to R, each chapter is driven by a research question, and empirical data analysis is used to provide answers to that question. These examples are data-driven inquiries that promote interaction between statistical methods and ideas and computer application. Computer code and output are interwoven in the book to illustrate exactly how each analysis is carried out and how output is interpreted. Additional topical coverage includes: Data exploration of one variable and multivariate data Comparing two groups and many groups Permutation tests, randomization tests, and the independent samples t-Test Bootstrap tests and bootstrap intervals Interval estimates and effect sizes Throughout the book, the authors incorporate data from real-world research studies as well aschapter problems that provide a platform to perform data analyses. A related Web site features a complete collection of the book's datasets along with the accompanying codebooks and the R script files and commands, allowing readers to reproduce the presented output and plots. Comparing Groups: Randomization and Bootstrap Methods Using R is an excellent book for upper-undergraduate and graduate level courses on statistical methods, particularlyin the educational and behavioral sciences. The book also serves as a valuable resource for researchers who need a practical guide to modern data analytic and computational methods.