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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.
Book Description
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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24 人中、11人の方が、｢このレビューが参考になった｣と投票しています。
形式:ペーパーバック
実証主義の立場から実際に社会研究を行う際のガイドラインを定めた書物であり、（特に日本の学部・大学院レベルにおける政治学教育の現状を考えた場合）その観点からは貴重な業績であると言える。しかし、その基礎付けは Carl Hempel らオーストリア学派の論理実証主義者に Popper を接木した時代遅れな代物であって、70年代以降になされた言語理論・科学哲学上の革新（後期Whitgensteinなど）をフォローしてはいない。従ってこの著作は実証主義とは何かを知るには適しているが、そもそも何故実証主義にもとづいて社会研究をなさねばならないのかに疑問を抱く者は他(Anthony Giddens etc.)をあたる必要があるだろう。
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26 人中、25人の方が、｢このレビューが参考になった｣と投票しています。
This not a stats book
2005/10/17
形式:ペーパーバック
This is a response to reviewers who think this is a stat book. This book is not meant to serve as a stats textbook (if you want one there are plenty of good ones written by statisticians and econometricians). This book is designed to serve as a guide to research design in social science in terms of developing a question, following systematic research procedures and measurement while using qualitative research methods. In that regard it does not do a great job as they are stuck up with applying simplistic statistical techniques (predominantly regression analysis)to qualitative methodology. As a result the work ends up appearing weak to both the statistically inclined (including myself) and those who use predominantly qualitative methods. Arguably the biggest problems with this work is in their treatment of constant dependent variable designs. This arises from their notion of a "causal effect" that is quite different from what qualitative researchers might see as causality. In statistical terms their notion is correct but when we move towards a qualitative interpretation of the same the concept becomes problematic primarily because it is difficult to discern the appropriate differentation between values of the dependent variable in qualitative work.
Nonetheless, this book should be treated on its own terms for attempting to synthesize quantiative and qualitative research methods. This book started a controversy that continues till this day and did a great job in forcing people to actually think more deeply about their research design and methods.
If you want to study statistics or econometrics forget this book (choose what you want to know about....regression analysis, time-series models, bayesian models....your choice). If you want to study qualitative research well read this book but then read Brady and Collier 2002 and George and Bennett 2004. George and Bennett's work is arguably the best book on research design I have ever read.
Nonetheless, this book should be treated on its own terms for attempting to synthesize quantiative and qualitative research methods. This book started a controversy that continues till this day and did a great job in forcing people to actually think more deeply about their research design and methods.
If you want to study statistics or econometrics forget this book (choose what you want to know about....regression analysis, time-series models, bayesian models....your choice). If you want to study qualitative research well read this book but then read Brady and Collier 2002 and George and Bennett 2004. George and Bennett's work is arguably the best book on research design I have ever read.
33 人中、29人の方が、｢このレビューが参考になった｣と投票しています。
Contrary to what my colleague from the Netherlands thinks...
2001/6/6
形式:ペーパーバック
Hands down, this is one of the best texts of qualitative methodology available for the political scientist. The ideas and arguments made in this volume are very pertinent to study creation. Moreover, King et al. are both willing and able to criticize one of the most common logical fallacies that we find in the literature: the misuse of inference. What my colleague from the Netherlands overlooks is the clear and oft-stated differentiation between correlation and how it applies to THEORIES OF CAUSATION. By not reading the text in a clear way, my colleague has also confused the issue of theory vs. hypothesis as well as the focus of the work on testing hypotheses derived from theories objectively. The mathematical notations used are SPECIFIED as only being applicable in the abstract. In fact, one does not need the math to understand the points made. Moreover, my colleague notes that there are some problems with categorization, despite the fact that King et al acknowledge that if you can't categorize it or find data on it, then you should change your hypotheses and try again. Quite honestly, I question whether or not this gentleman bothered to read the book. I don't see how the points made in this volume could be any clearer. I would recommend this book to anyone seeking an all encompassing approach to qualitative analysis. However, if you are a person that sees little or no value to testing theories or are very polarized in the qualitative vs. quantitative debate, then you are most likely better off reading a good novel than this book.
36 人中、31人の方が、｢このレビューが参考になった｣と投票しています。
Want to Avoid Being Hoodwinked? Here's A Way To Learn!
1998/8/7
形式:ペーパーバック
Especially in an election year, the careful and critical examination of public policy and statistical findings is essential. In "Designing Inquiry..." King, Verba and Keohane explain basic statistical and methodological concepts previously only understandable to those studying the advanced social sciences. Concepts such as "endogeneity" and other logical fallacies are explained in language that is easy for the layman to understand, and in enough detail to be a gem for experts in the social sciences. The book explains in simple detail concepts that could be used by anyone to fairly evaluate the results of any study, and does it in a way that anyone can understand. Given the fact that many studies are passed off as "scientific" by journalists, politicians, and special interest groups when, in reality, they are fundamentally flawed, this book offers anyone the opportunity to learn how to critically evaluate studies, and how to reject studies t! hat are often utilized more to fool the voting public and appeal to emotion rather than logic. This book is one of the most significant ones of the decade, and should be read by all wanting to critically participate in a world where the term "scientific study" is often used more as an attempt to convince people of flawed findings rather than logically grounded results.
Sean A. McKitrick
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