Designing Social Inquiry

Rating:
Summary: Contrary to what my colleague from the Netherlands thinks...
Review: 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.

Rating:
Summary: Contrary to what my colleague from the Netherlands thinks...
Review: 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.

Rating:
Summary: Controversial and in desperate need of editing
Review: King, Keohane and Verba (KKV) present an argument for unifying qualitative and quantitative methodologies in political science under one overall rubric. However, the book falls short in several respects.

First, KKV have a tendency to repeat themselves. They say the same thing over and over in different ways. In other words, they replicate what they just said. Duplication is a big problem as well. (Get the hint yet?) More editing would have helped.

Second, not everything they say can be accepted at face value. They take seemingly innocent ideas and state definitive conclusions, without letting the reader know that what they're saying overturns years of epistemological research into the nature of scientific research. People who disagree with their perspective are brushed to the side.

Third, their attempt to unify qualitative and quantitative methods suffers from a bias to the quantitative side of things. They first explain ideas in quantitative or statistical terms, use a formal analysis, and then state something like, "the same method can be used in qualitative analysis" without always saying how, precisely, that should be accomplished. Sometimes, I grant, they provide qualitative examples, but those serve primarily as foils against which they base their hypothesis. Qualitative researchers quoted by them tend to get torn to shreds by the end.

This book is usually required reading in research design/ research methods courses because it's been the source of most disagreements in political science methodology over the 10 years since its publication. But if you don't have to read it for a class, don't bother.

Rating:
Summary: The worst book I've ever read in methodology or in stats
Review: Many books contain errors --usually typos or other small ones. The book by King and others, however, really takes the biscuit, by making fundamental malinterpretations of statistics and methodology. The book aims at proposing a research methodology for both qualitative and quantitative research. The result, however, you wouldn't want to show to your undergraduate students. The most annoying malinterpretations for a social scientist are probably the following. First, relying on Pearson's 1892 (!) monograph, King e.a. state that method is more important than content of science. Apparently, nothing more has been learned in the last 120 years. Second, correlation is malinterpreted as causation. This is something you can't take for serious, especially when it is proposed in the introductory chapters and heavily used in the rest of the book. Third, some assumptions are proposed that your data should meet. These assumptions only apply to some sense to the statistical 'ordinary least squares' (OLS), but even in stats or econometrics these assumptions can be by-passed by using other estimation techniques. Furthermore, how would you test homogeneity in your cross-section when your qualitative reseach focuses on, e.g., motives of actors, while you cannot categorise that variable? Fourth, decision rules are proposed for 'constructing causal theories'. King e.a. seem to unconsiously mislead the innocent reader by mixing the concepts of 'hypothesis' and 'theory'. Fifth, some more assumptions concerning data quality are heavily misleading, and at most apply to OLS, but can easily be solved by using other estimation techniques. Some last bloopers: 'A research desing that explains a lot with a lot is not very informative' (p. 123); this is nonsense as long as long as your degrees of freedom are sufficient, and you don't face multicollinearity; 'Abstract, unobserved concepts [...] can be a hindrance to empirical valuation [...] unless they can be defined in such a way that they can be observed and measured' (p.109). This statement completely ignores that research on latent variables as, e.g., done by Maddala or others in the 1980s and more recently.

In sum, if you wish to buy a book on methodology: buy a book on methodology, written by a methodologist, and not by some political scientists. If you wish to get some introduction into the field of statistics or econometrics, then buy ANY other book that has a title as 'introductory econometrics' or similar. In either case, don't spend your money on this one.

Rating:
Summary: Typically fake statistics
Review: This book is the typical fake statistics written by political scientists who do not know that they are talking about to political scientists who will never know about the true statistics. Do not waste your money and time on such junks. Another book to avoid: unifying political methodology by Gary King. Spend your money and time on books written by real statisticians instead. Learn first hand from those who know.