Download or read book Social Inquiry and Bayesian Inference written by Tasha Fairfield and published by Cambridge University Press. This book was released on 2022-08-04 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides guidance for Bayesian updating in case study, process-tracing, and comparative research, in order to refine intuition and improve inferences from qualitative evidence.
Download or read book Designing Social Inquiry written by Gary King and published by Princeton University Press. This book was released on 1994-05-22 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing Social Inquiry focuses on improving qualitative research, where numerical measurement is either impossible or undesirable. What are the right questions to ask? How should you define and make inferences about causal effects? How can you avoid bias? How many cases do you need, and how should they be selected? What are the consequences of unavoidable problems in qualitative research, such as measurement error, incomplete information, or omitted variables? What are proper ways to estimate and report the uncertainty of your conclusions?
Download or read book Rethinking Social Inquiry written by Henry E. Brady and published by Rowman & Littlefield Publishers. This book was released on 2010-09-16 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: With innovative new chapters on process tracing, regression analysis, and natural experiments, the second edition of Rethinking Social Inquiry further extends the reach of this path-breaking book. The original debate with King, Keohane, and Verba_now updated_remains central to the volume, and the new material illuminates evolving discussions of essential methodological tools. Thus, process tracing is often invoked as fundamental to qualitative analysis, but is rarely applied with precision. Pitfalls of regression analysis are sometimes noted, but often are inadequately examined. And the complex assumptions and trade-offs of natural experiments are poorly understood. The second edition extends the methodological horizon through exploring these critical tools. A distinctive feature of this edition is the online placement of four chapters from the prior edition, all focused on the dialogue with King, Keohane, and Verba. Also posted online are exercises for teaching process tracing and understanding process tracing.
Download or read book Ecological Inference written by Gary King and published by Cambridge University Press. This book was released on 2004-09-13 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing upon the recent explosion of research in the field, a diverse group of scholars surveys the latest strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays offers many fresh and important contributions to the study of ecological inference.
Download or read book Process Tracing written by Andrew Bennett and published by Cambridge University Press. This book was released on 2015 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides empirically grounded conceptual, design and practical advice on conducting process tracing, a key method of qualitative research.
Download or read book Natural Experiments in the Social Sciences written by Thad Dunning and published by Cambridge University Press. This book was released on 2012-09-06 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive guide to natural experiments, providing an ideal introduction for scholars and students.
Download or read book The Production of Knowledge written by Colin Elman and published by Cambridge University Press. This book was released on 2020-03-19 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: A wide-ranging discussion of factors that impede the cumulation of knowledge in the social sciences, including problems of transparency, replication, and reliability. Rather than focusing on individual studies or methods, this book examines how collective institutions and practices have (often unintended) impacts on the production of knowledge.
Download or read book Rethinking Comparison written by Erica S. Simmons and published by Cambridge University Press. This book was released on 2021-10-07 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Statistics for Experimental Scientists written by Richard A. Chechile and published by MIT Press. This book was released on 2020-09-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis. This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book's premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics.
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Download or read book A Solution to the Ecological Inference Problem written by Gary King and published by Princeton University Press. This book was released on 2013-09-20 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a solution to the ecological inference problem, which has plagued users of statistical methods for over seventy-five years: How can researchers reliably infer individual-level behavior from aggregate (ecological) data? In political science, this question arises when individual-level surveys are unavailable (for instance, local or comparative electoral politics), unreliable (racial politics), insufficient (political geography), or infeasible (political history). This ecological inference problem also confronts researchers in numerous areas of major significance in public policy, and other academic disciplines, ranging from epidemiology and marketing to sociology and quantitative history. Although many have attempted to make such cross-level inferences, scholars agree that all existing methods yield very inaccurate conclusions about the world. In this volume, Gary King lays out a unique--and reliable--solution to this venerable problem. King begins with a qualitative overview, readable even by those without a statistical background. He then unifies the apparently diverse findings in the methodological literature, so that only one aggregation problem remains to be solved. He then presents his solution, as well as empirical evaluations of the solution that include over 16,000 comparisons of his estimates from real aggregate data to the known individual-level answer. The method works in practice. King's solution to the ecological inference problem will enable empirical researchers to investigate substantive questions that have heretofore proved unanswerable, and move forward fields of inquiry in which progress has been stifled by this problem.
Download or read book Multi Method Social Science written by Jason Seawright and published by Cambridge University Press. This book was released on 2016-09-08 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first systematic guide to designing multi-method research, considering a wide range of statistical and qualitative tools.
Download or read book A Tale of Two Cultures written by Gary Goertz and published by Princeton University Press. This book was released on 2012-09-09 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some in the social sciences argue that the same logic applies to both qualitative and quantitative methods. In A Tale of Two Cultures, Gary Goertz and James Mahoney demonstrate that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. They identify and discuss major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, Goertz and Mahoney also seek to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. This book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.
Download or read book Integrated Inferences written by Macartan Humphreys and published by Cambridge University Press. This book was released on 2023-10-31 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces a Bayesian approach to the use of causal models to design and carry out qualitative and mixed-methods research. Addressed to researchers across the social sciences, this book shows how causal models allow us to combine extensive and intensive data strategies to answer both general and case-specific causal questions.
Download or read book Finding Your Social Science Project written by John Gerring and published by Cambridge University Press. This book was released on 2022-10-13 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to finding your research topic, applicable to all fields of social science.
Download or read book Bayesian Analysis for the Social Sciences written by Simon Jackman and published by John Wiley & Sons. This book was released on 2009-10-27 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS – the most-widely used Bayesian analysis software in the world – and R – an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.
Download or read book Bayesian Networks in Educational Assessment written by Russell G. Almond and published by Springer. This book was released on 2015-03-10 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics. This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
