Designing Social Inquiry: Scientific Inference in Qualitative Research

Princeton University Press
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While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research performed in this field. These leading scholars, each representing diverse academic traditions, have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. Their book demonstrates that the same logic of inference underlies both good quantitative and good qualitative research designs, and their approach applies equally to each.

Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and uncertainty of empirical inferences, discovering causal effects, and generally improving qualitative research. Among the specific topics they address are interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed. The unified logic of inference that this book explicates will be enormously useful to qualitative researchers of all traditions and substantive fields.

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About the author

Gary King is Professor of Government and Director of the Harvard Data Center at Harvard University. Robert O. Keohane is Stanfield Professor of International Peace at Harvard University. Sidney Verba is Carl H. Pforzheimer University Professor and Director of the Harvard University Library.
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Additional Information

Publisher
Princeton University Press
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Published on
May 2, 1994
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Pages
264
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ISBN
9781400821211
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Language
English
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Genres
Social Science / Methodology
Social Science / Research
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Content Protection
This content is DRM protected.
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Available on Android devices
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Eligible for Family Library

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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.

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.

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