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Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis [Minkštas viršelis]

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, (Central European University, Budapest)
  • Formatas: Paperback / softback, 370 pages, aukštis x plotis x storis: 244x173x18 mm, weight: 700 g, 55 Tables, black and white; 37 Line drawings, unspecified
  • Serija: Strategies for Social Inquiry
  • Išleidimo metai: 30-Aug-2012
  • Leidėjas: Cambridge University Press
  • ISBN-10: 1107601134
  • ISBN-13: 9781107601130
Kitos knygos pagal šią temą:
Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative AnalysisDidesnis paveikslėlis
  • Formatas: Paperback / softback, 370 pages, aukštis x plotis x storis: 244x173x18 mm, weight: 700 g, 55 Tables, black and white; 37 Line drawings, unspecified
  • Serija: Strategies for Social Inquiry
  • Išleidimo metai: 30-Aug-2012
  • Leidėjas: Cambridge University Press
  • ISBN-10: 1107601134
  • ISBN-13: 9781107601130
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781107601130.html
Raktažodžiai:
Qualitative Comparative Analysis (QCA) and other set-theoretic methods distinguish themselves from other approaches to the study of social phenomena by using sets and the search for set relations. In virtually all social science fields, statements about social phenomena can be framed in terms of set relations, and using set-theoretic methods to investigate these statements is therefore highly valuable. This book guides readers through the basic principles of set theory and then on to the applied practices of QCA. It provides a thorough understanding of basic and advanced issues in set-theoretic methods together with tricks of the trade, software handling and exercises. Most arguments are introduced using examples from existing research. The use of QCA is increasing rapidly and the application of set-theory is both fruitful and still widely misunderstood in current empirical comparative social research. This book provides the comprehensive guide to these methods for researchers across the social sciences.

Recenzijos

'We have long needed a volume that comprehensively, clearly, and systematically covers Boolean and fuzzy set methodologies. Schneider and Wagemann have filled this need with their book, and it will certainly play a central role in guiding research and teaching.' Gary Goertz, University of Arizona 'For relationships that can be viewed in terms of sufficiency or necessity, set-theory provides a powerful tool to model causality. QCA, in its various forms, provides a bridge between single case studies and quantitative analysis of linkages among interval-level or ratio variables across multiple cases by providing the tools to examine relationships in set-theoretic terms among dichotomies or concepts defined as fuzzy sets. This clearly written and comprehensive introduction to QCA, which insists on causal analyses that are explicitly intended to study possible multiple pathways to given outcomes, is must-reading for social scientists who wish to expand their methodological horizons and get away from the all too common 'throw as many variables as possible into the regression hopper and see which ones come up statistically significant' form of barefoot empiricism.' Bernie Grofman, University of California, Irvine 'This is the first volume that bridges the fundamentals of set-theoretic methods with the many ongoing innovations. A must for anyone aiming to exploit the full potential of the QCA toolbox.' Benoīt Rihoux, Université catholique de Louvain, Belgium, and COMPASSS international network

Daugiau informacijos

A 'user's guide' to Qualitative Comparative Analysis (QCA) and the methodological family of set-theoretic methods in social science.
List of figures
xii
List of tables
xiv
Acknowledgements xvi
Introduction 1(20)
Set-theoretic approaches in the social sciences
1(7)
Qualitative Comparative Analysis as a set-theoretic approach and technique
8(5)
Variants of QCA
13(3)
Plan of the book
16(3)
How to use this book
19(2)
Part I Set-theoretic methods: the basics
21(96)
1 Sets, set membership, and calibration
23(19)
1.1 The notion of sets
24(8)
1.1.1 Sets and concepts
24(1)
1.1.2 The pros and cons of crisp sets
24(3)
1.1.3 Properties of fuzzy sets
27(3)
1.1.4 What fuzzy sets are not
30(2)
1.2 The calibration of set membership
32(10)
1.2.1 Principles of calibration
32(1)
1.2.2 The use of quantitative scales for calibration
33(2)
1.2.3 The "direct" and "indirect" methods of calibration
35(3)
1.2.4 Does the choice of calibration strategy matter much?
38(2)
1.2.5 Assessing calibration
40(2)
2 Notions and operations in set theory
42(14)
2.1 Conjunctions, Boolean and fuzzy multiplication, intersection, logical AND
42(3)
2.2 Disjunctions, Boolean and fuzzy addition, union, logical OR
45(2)
2.3 Negations, complements, logical NOT
47(1)
2.4 Operations on complex expressions
47(5)
2.4.1 Rules for combining logical operators
48(1)
2.4.2 Negation, intersection, and union of complex sets
49(2)
2.4.3 Calculating membership in complex sets
51(1)
2.5 Relations between sets
52(2)
2.6 Notational systems in set-theoretic methods
54(2)
3 Set relations
56(35)
3.1 Sufficient conditions
57(12)
3.1.1 Crisp sets
57(8)
3.1.2 Fuzzy sets
65(4)
3.2 Necessary conditions
69(7)
3.2.1 Crisp sets
69(6)
3.2.2 Fuzzy sets
75(1)
3.3 Causal complexity in set-theoretic methods
76(15)
3.3.1 Defining causal complexity
78(1)
3.3.2 INUS and SUIN conditions
79(2)
3.3.3 The notion of asymmetry
81(2)
3.3.4 Set-theoretic methods and standard quantitative approaches
83(8)
4 Truth tables
91(26)
4.1 What is a truth table?
92(1)
4.2 How to get from a data matrix to a truth table
93(11)
4.2.1 Crisp sets
93(3)
4.2.2 Fuzzy sets
96(8)
4.3 Analyzing truth tables
104(13)
4.3.1 Matching similar conjunctions
105(3)
4.3.2 Logically redundant prime implicants
108(4)
4.3.3 Issues related to the analysis of the non-occurrence of the outcome
112(5)
Part II Neat formal logic meets noisy social science data
117(78)
5 Parameters of fit
119(32)
5.1 Defining and dealing with contradictory truth table rows
120(3)
5.2 Consistency of sufficient conditions
123(6)
5.3 Coverage of sufficient conditions
129(10)
5.4 Consistency of necessary conditions
139(5)
5.5 Coverage of necessary conditions
144(4)
5.6 Issues related to consistency and coverage
148(3)
6 Limited diversity and logical remainders
151(27)
6.1 Limited diversity in set-theoretic methods: how to see it when it is there
152(1)
6.2 Sources of limited diversity
153(4)
6.2.1 Arithmetic remainders
154(1)
6.2.2 Clustered remainders
154(1)
6.2.3 Impossible remainders
155(2)
6.3 What limited diversity is not
157(3)
6.4 The Standard Analysis procedure: identifying logical remainders for crafting plausible solution terms
160(18)
6.4.1 The dimension of set relations
161(4)
6.4.2 The dimension of complexity
165(2)
6.4.3 The dimension of types of counterfactuals
167(8)
6.4.4 The Standard Analysis procedure in a nutshell
175(3)
7 The Truth Table Algorithm
178(17)
7.1 From the data matrix to truth table
179(3)
7.2 Attributing an outcome value to each truth table row
182(4)
7.3 Logically minimizing the truth table
186(4)
7.4 Implications of the Truth Table Algorithm
190(5)
Part III Potential pitfalls and suggestions for solutions
195(56)
8 Potential pitfalls in the Standard Analysis procedure and suggestions for improvement
197(23)
8.1 Beyond the Standard Analysis: expanding the types of counterfactuals
198(2)
8.2 The Enhanced Standard Analysis: forms of untenable assumptions and how to avoid them
200(11)
8.2.1 Incoherent counterfactuals I: contradicting the statement of necessity
201(2)
8.2.2 Incoherent counterfactuals II: contradictory assumptions
203(3)
8.2.3 Implausible counterfactuals: contradicting common sense
206(3)
8.2.4 Putting the Enhanced Standard Analysis procedure into practice
209(2)
8.3 Theory-Guided Enhanced Standard Analysis: complementary strategies for dealing with logical remainders
211(6)
8.3.1 Choosing entire truth table rows as good counterfactuals
212(3)
8.3.2 Formulating conjunctural directional expectations
215(2)
8.4 Comparing the different strategies for the treatment of logical remainders
217(3)
9 Potential pitfalls in the analysis of necessity and sufficiency and suggestions for avoiding them
220(31)
9.1 Pitfalls in inferring necessity from sufficiency solution terms
221(11)
9.1.1 Hidden necessary conditions
221(6)
9.1.2 The appearance of false necessary conditions
227(5)
9.2 The analytic consequences of skewed set-membership scores
232(19)
9.2.1 The coverage of necessary conditions and the problem of trivialness
233(4)
9.2.2 The consistency of sufficient conditions and the problem of simultaneous subset relations
237(7)
9.2.3 A general treatment of skewed set membership in fuzzy-set analyses
244(7)
Part IV Variants of QCA as a technique meet QCA as an approach
251(71)
10 Variants of QCA
253(22)
10.1 The two-step approach
253(2)
10.2 Multi-value QCA
255(8)
10.2.1 Principles of mvQCA: notation and logical minimization
256(2)
10.2.2 An assessment of mvQCA
258(5)
10.3 Set-theoretic methods and time
263(12)
10.3.1 Forms of causally relevant notions of time
264(1)
10.3.2 Informal ways of integrating notions of time into set-theoretic methods
265(1)
10.3.3 Sequence elaboration
266(3)
10.3.4 Temporal QCA
269(6)
11 Data analysis technique meets set-theoretic approach
275(38)
11.1 Recipe for a good QCA
275(9)
11.1.1 The appropriateness of set-theoretic methods
276(1)
11.1.2 The choice of the conditions and the outcome
276(1)
11.1.3 The choice of the QCA variant
277(1)
11.1.4 Calibration of set-membership scores
277(1)
11.1.5 Analysis of necessary conditions
278(1)
11.1.6 Analysis of sufficient conditions
278(2)
11.1.7 Presentation of results
280(1)
11.1.8 Interpretation of results
280(1)
11.1.9 Reiteration of the research cycle
281(1)
11.1.10 The use of software
282(2)
11.2 Robustness and uncertainty in QCA
284(11)
11.2.1 How do we see robustness in set-theoretic methods when it is there?
285(2)
11.2.2 The effects of changing calibration
287(4)
11.2.3 The effects of changing consistency levels
291(2)
11.2.4 The effect of dropping or adding cases
293(2)
11.3 The evaluation of theories in set-theoretic methods
295(10)
11.3.1 Why standard hypothesis testing does not fit into set-theoretic methods
296(1)
11.3.2 The basics of theory evaluation in set-theoretic methods
297(3)
11.3.3 Extending theory evaluation by integrating consistency and coverage
300(4)
11.3.4 Summarizing set-theoretic theory evaluation
304(1)
11.4 Set-theoretic methods and case selection
305(8)
11.4.1 Types of cases after a QCA
306(2)
11.4.2 Forms and aims of (comparative) within-case studies after a QCA
308(2)
11.4.3 Post-QCA case selection principles
310(3)
12 Looking back, looking ahead
313(9)
12.1 Looking back: the main topics of this book
313(3)
12.2 Myths and misunderstandings
316(2)
12.3 Looking ahead: tasks and developments in the coming years
318(4)
Glossary 322(14)
Bibliography 336(10)
Index 346
Carsten Q. Schneider is Associate Professor in the Department of Political Science and Founding Director of the Center for the Study of Imperfections in Democracies at Central European University, Hungary. Claudius Wagemann is Lecturer in the Doctoral Program in Political Science at the Istituto Italiano di Scienze Umane (SUM), Florence.