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E-grāmata: Systematic Mixed-Methods Research for Social Scientists

  • Formāts: EPUB+DRM
  • Izdošanas datums: 28-Jul-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • Valoda: eng
  • ISBN-13: 9783030931483
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Systematic Mixed-Methods Research for Social ScientistsPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 28-Jul-2022
  • Izdevniecība: Springer Nature Switzerland AG
  • Valoda: eng
  • ISBN-13: 9783030931483
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This textbook provides clear and accessible guidance on the importance and practical application of mixed-methods research. Professor Olsen presents a range of multiple mixed-methods techniques using quantified data. Critical realism underpins key arguments. She offers detailed examples based on wide experience with international applied social-science projects. 

The book shows readers how to join quantitative and qualitative data together. Detailed methods include: using multiple-level data; constructing new indices based on mixing survey responses and personal interviews; and using focus groups alongside a large survey. The book provides readers with linkages of data between different software packages. It explains the analysis stage in mixed-methods research, interprets complex causality, shows how to transform data, and helps with interpreting social structures, institutions, and discourses. Finally, the book covers some epistemological issues. These include the nature and value of data. The author discusses validity and techniques for ensuring relevant, innovative conclusions. The book also touches on action research as an overarching participatory method.

This book is based on clear and explicit definitions, is accessible to students and researchers across disciplines, and shows the appeal of mixed-methods research to those trained in quantitative methods.
Part I Setting Up Systematic Mixed Methods Research (SMMR)
1(56)
1 Mixed Methods for Research on Open Systems
3(30)
1.1 The Link Between Quantification and Mixed Methods
4(4)
1.2 A Conceptual Introduction to Methodology and Ontology
8(10)
1.3 Triangulation
18(2)
1.4 Three Domains of Reality, As Realists Approach Research
20(7)
1.5 Conclusion
27(6)
Appendix
29(1)
References
29(4)
2 Mixed Methods with Weakly Structuralist Regression Models
33(24)
2.1 Modelling and Methodology for Mixed Methods
34(9)
2.2 Strategic Structuralism
43(5)
2.3 Logics Used in Strategic Structuralist Research
48(3)
2.4 Conclusion
51(6)
Appendix
52(2)
References
54(3)
Part II SMMR Approaches in Practical Terms
57(144)
3 Causality in Mixed-Methods Projects That Use Regression
59(20)
3.1 Causality in a Regression Model
60(5)
3.2 Stages of Research Design Amendment for Mixed-Methods Research
65(1)
3.3 Deduction Cannot Stand Alone
66(2)
3.4 A Quantitatively Complex Example
68(6)
3.5 Conclusion
74(5)
References
76(3)
4 Multiple Logics in Systematic Mixed-Methods Research
79(30)
4.1 Multiple Logics in Statistical Research: Some Exemplars
81(8)
4.2 An Exemplar Using Participatory Research with Panel Data
89(2)
4.3 A Statistical Exemplar with a Randomised Control Trial for a Social Intervention
91(6)
4.4 Warranted Arguments and Two Caveats for Strategic Structuralism
97(1)
4.5 An Exemplar Using Correspondence Analysis Without Regression
98(11)
Appendix
103(4)
References
107(2)
5 Factor Analysis in a Mixed-Methods Context
109(22)
5.1 Latent Variables and Entities
109(7)
5.2 One Could Use Exploratory or Confirmatory Factor Analysis
116(2)
5.3 Measurement Issues for the Manifest Variables in a Confirmatory Model
118(1)
5.4 Mixed-Methods Research Designs Using Latent Variables
119(1)
5.5 Whether to Use Scoping Analysis or Primary Field Research
120(2)
5.6 Research Scope and Feedback Loops
122(1)
5.7 Closed and Open Retroduction in a Factor Analysis Context
123(3)
5.8 The Ontological Element
126(1)
5.9 Conclusion
126(5)
References
128(3)
6 Qualitative Comparative Analysis (QCA): A Classic Mixed Method Using Theory
131(26)
6.1 QCA Is an Umbrella Over Many Procedures
134(2)
6.2 Tables Help to Summarise Qualitative Comparative Evidence
136(5)
6.3 Data Reduction Has Been Well Theorised
141(6)
6.4 Threshold Tests, Quasi-Sufficiency, and Next Steps in QCA
147(1)
6.5 Conclusion
148(9)
Appendix
149(5)
References
154(3)
7 Calibration of Fuzzy Sets, Calibration of Measurement: A Realist Synthesis
157(18)
7.1 Two Forms of Calibration: Ordered Categories or Fuzzy Sets
158(5)
7.2 Features of Multiple Hypothesis Tests Using Fuzzy Sets
163(1)
7.3 Asymmetry of the Causal Mechanisms? Issues Around Counterfactuals
163(4)
7.4 How to Make and Illustrate Deep Linkages
167(8)
Appendix
169(4)
References
173(2)
8 From Content Analysis to Discourse Analysis: Using Systematic Analysis of Meanings and Discourses
175(26)
8.1 Methods of Qualitative Analysis and Elaboration of Findings
176(1)
8.2 Qualitative Methods, with a Content Analysis Example
176(5)
8.3 Three Illustrations Demonstrating Deep Arguments Based on Depth Ontology
181(14)
8.4 Conclusion
195(6)
Appendix
198(1)
References
198(3)
Part III Interpretation and the Validity of Research
201(42)
9 Interpretations, Meanings, and Validity in Mixed-Methods Research
203(20)
9.1 Truth Is Not Simple in a Complex Society
203(7)
9.2 Epistemology for Late-Modern Mixed Methods
210(3)
9.3 Falsifying Hypotheses: Possible and Desirable, but Not Necessary
213(4)
9.4 A Retroductive Approach
217(2)
9.5 Conclusion
219(4)
References
220(3)
10 Summary of the Logics and Methods for Systematic Mixed-Methods Research
223(12)
10.1 Induction
224(1)
10.2 Deduction
225(2)
10.3 Retroduction
227(1)
10.4 Synthesis
228(1)
10.5 Recognising Relevant Irreducible Phenomena (Holism)
229(1)
10.6 Logical Linkage
230(1)
10.7 Conclusion
231(4)
References
233(2)
11 Glossary
235(8)
Index 243
Wendy Olsen is Professor of Socio-Economics at the University of Manchester, UK. She researches employment, informal work, gender, norms, and labour markets. Her books include Rural Indian Social Relations (1996), Realist Methodology (ed., 4 volumes, 2010), and Data Collection (2012). 
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