Systematic Mixed-Methods Research for Social Scientists

✍ Scribed by Wendy Olsen

• Publisher: Palgrave Macmillan
• Year: 2022
• Tongue: English
• Leaves: 256
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Preface
How to Use This Book
Acknowledgements
Contents
Abbreviations
List of Figures
List of Tables
Introduction
Part I: Setting Up Systematic Mixed Methods Research (SMMR)
1: Mixed Methods for Research on Open Systems
1.1 The Link Between Quantification and Mixed Methods
1.2 A Conceptual Introduction to Methodology and Ontology
Key Terminology
An Illustration of Reflexivity About a Bar Chart
1.3 Triangulation
1.4 Three Domains of Reality, As Realists Approach Research
Open Systems
Distinguishing Reality and the Empirical
Three Domains of Reality
Retroduction (See Also Glossary)
Forms of Integration of Mixed Methods
1.5 Conclusion
Appendix
References
2: Mixed Methods with Weakly Structuralist Regression Models
2.1 Modelling and Methodology for Mixed Methods
Three Exemplars: A Range of Warranted Mixed-Methods Arguments
Fourth Exemplar: Qualitative Online Data with Fuzzy Sets, Using Administrative Data
2.2 Strategic Structuralism
2.3 Logics Used in Strategic Structuralist Research
2.4 Conclusion
Appendix
References
Part II: SMMR Approaches in Practical Terms
3: Causality in Mixed-Methods Projects That Use Regression
3.1 Causality in a Regression Model
A S I M E (Structural-Institutional-Mechanisms-Event) Heuristic Framework For Regression
3.2 Stages of Research Design Amendment for Mixed-Methods Research
3.3 Deduction Cannot Stand Alone
3.4 A Quantitatively Complex Example
3.5 Conclusion
References
4: Multiple Logics in Systematic Mixed-Methods Research
4.1 Multiple Logics in Statistical Research: Some Exemplars
4.2 An Exemplar Using Participatory Research with Panel Data
4.3 A Statistical Exemplar with a Randomised Control Trial for a Social Intervention
4.4 Warranted Arguments and Two Caveats for Strategic Structuralism
4.5 An Exemplar Using Correspondence Analysis Without Regression
Regression and MCA Can Be Grounded on Weak Structuralism
Appendix
References
5: Factor Analysis in a Mixed-Methods Context
5.1 Latent Variables and Entities
5.2 One Could Use Exploratory or Confirmatory Factor Analysis
5.3 Measurement Issues for the Manifest Variables in a Confirmatory Model
5.4 Mixed-Methods Research Designs Using Latent Variables
5.5 Whether to Use Scoping Analysis or Primary Field Research
5.6 Research Scope and Feedback Loops
5.7 Closed and Open Retroduction in a Factor Analysis Context
5.8 The Ontological Element
5.9 Conclusion
References
6: Qualitative Comparative Analysis (QCA): A Classic Mixed Method Using Theory
6.1 QCA Is an Umbrella Over Many Procedures
6.2 Tables Help to Summarise Qualitative Comparative Evidence
6.3 Data Reduction Has Been Well Theorised
6.4 Threshold Tests, Quasi-Sufficiency, and Next Steps in QCA
6.5 Conclusion
Appendix
References
7: Calibration of Fuzzy Sets, Calibration of Measurement: A Realist Synthesis
7.1 Two Forms of Calibration: Ordered Categories or Fuzzy Sets
7.2 Features of Multiple Hypothesis Tests Using Fuzzy Sets
7.3 Asymmetry of the Causal Mechanisms? Issues Around Counterfactuals
7.4 How to Make and Illustrate Deep Linkages
In Conclusion: Pluralism and Encompassing Research Are Superior Methods
Appendix
References
8: From Content Analysis to Discourse Analysis: Using Systematic Analysis of Meanings and Discourses
8.1 Methods of Qualitative Analysis and Elaboration of Findings
8.2 Qualitative Methods, with a Content Analysis Example
8.3 Three Illustrations Demonstrating Deep Arguments Based on Depth Ontology
Example 8A: Epistemology and Discourse Analysis of a Database with NVivo Coding
Example 8B: Rural Women and Work in a South Asian Context
Example 8C: Discourses of Sri Lankan Banking Using NVivo Coding Across Genres
8.4 Conclusion
Appendix
References
Part III: Interpretation and the Validity of Research
9: Interpretations, Meanings, and Validity in Mixed-Methods Research
9.1 Truth Is Not Simple in a Complex Society
9.2 Epistemology for Late-Modern Mixed Methods
9.3 Falsifying Hypotheses: Possible and Desirable, but Not Necessary
9.4 A Retroductive Approach
9.5 Conclusion
References
10: Summary of the Logics and Methods for Systematic Mixed-Methods Research
10.1 Induction
10.2 Deduction
10.3 Retroduction
10.4 Synthesis
10.5 Recognising Relevant Irreducible Phenomena (Holism)
10.6 Logical Linkage
10.7 Conclusion
Generating New Research Ideas
References
11: Glossary
Index