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Author: Gary King
Publisher: Princeton University Press
ISBN: 1400849209
Category : Political Science
Languages : en
Pages : 366
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Book Description
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.
Author: Gary King
Publisher: Princeton University Press
ISBN: 1400849209
Category : Political Science
Languages : en
Pages : 366
Get Book Here
Book Description
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.
Author: Gary King
Publisher: Cambridge University Press
ISBN: 9780521542807
Category : Nature
Languages : en
Pages : 436
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Book Description
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.
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Languages : en
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Book Description
Cf.: http://dx.doi.org/10.3886/ICPSR01132.v1.
Author: David A. Freedman
Publisher: Cambridge University Press
ISBN: 0521195004
Category : Mathematics
Languages : en
Pages : 416
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Book Description
David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
Author: Gary King
Publisher: Princeton University Press
ISBN: 0691034710
Category : Social Science
Languages : en
Pages : 259
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Book Description
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?
Author: Micah Altman
Publisher: John Wiley & Sons
ISBN: 0471475742
Category : Mathematics
Languages : en
Pages : 349
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Book Description
At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.
Author: Alan E. Gelfand
Publisher: CRC Press
ISBN: 1498752128
Category : Mathematics
Languages : en
Pages : 876
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Book Description
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
Author: Benjamin M. Bolker
Publisher: Princeton University Press
ISBN: 0691125228
Category : Computers
Languages : en
Pages : 408
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Book Description
Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author: Roger Detels
Publisher: Oxford University Press
ISBN: 019881013X
Category : Medical
Languages : en
Pages : 1717
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Book Description
Sixth edition of the hugely successful, internationally recognised textbook on global public health and epidemiology, with 3 volumes comprehensively covering the scope, methods, and practice of the discipline
Author: Samuel Myers
Publisher: Island Press
ISBN: 1610919661
Category : Social Science
Languages : en
Pages : 538
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Book Description
Human health depends on the health of the planet. Earth’s natural systems—the air, the water, the biodiversity, the climate—are our life support systems. Yet climate change, biodiversity loss, scarcity of land and freshwater, pollution and other threats are degrading these systems. The emerging field of planetary health aims to understand how these changes threaten our health and how to protect ourselves and the rest of the biosphere. Planetary Health: Protecting Nature to Protect Ourselves provides a readable introduction to this new paradigm. With an interdisciplinary approach, the book addresses a wide range of health impacts felt in the Anthropocene, including food and nutrition, infectious disease, non-communicable disease, dislocation and conflict, and mental health. It also presents strategies to combat environmental changes and its ill-effects, such as controlling toxic exposures, investing in clean energy, improving urban design, and more. Chapters are authored by widely recognized experts. The result is a comprehensive and optimistic overview of a growing field that is being adopted by researchers and universities around the world. Students of public health will gain a solid grounding in the new challenges their profession must confront, while those in the environmental sciences, agriculture, the design professions, and other fields will become familiar with the human consequences of planetary changes. Understanding how our changing environment affects our health is increasingly critical to a variety of disciplines and professions. Planetary Health is the definitive guide to this vital field.
