Integrated Inferences: Causal Models for Qualitative and Mixed-Method Research

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Macartan Humphreys (Wissenschaftszentrum Berlin für Sozialforschung) Alan M. Jacobs (University of British Columbia, Vancouver)

Integrated Inferences

Causal Models for Qualitative and Mixed-Method Research

Macartan Humphreys (Wissenschaftszentrum Berlin für Sozialforschung), Alan M. Jacobs (University of British Columbia, Vancouver)

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English

Cambridge University Press
30 November 2023

Social research & statistics

Series: Strategies for Social Inquiry

There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.

By: Macartan Humphreys (Wissenschaftszentrum Berlin für Sozialforschung), Alan M. Jacobs (University of British Columbia, Vancouver)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
ISBN: 9781316620663
ISBN 10: 1316620662
Series: Strategies for Social Inquiry
Pages: 300
Publication Date: 30 November 2023
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

1. Introduction; I. Foundations: 2. Causal models; 3. Illustrating causal models; 4. Causal queries; 5. Bayesian answers; 6. Theories as causal models; II. Model-based causal inference: 7. Process tracing with causal models; 8. Process tracing applications; 9. Integrated inferences; 10. Integrated inferences applications; 11. Mixing models; III. Design choices: 12. Clue selection as a decision problem; 13. Case selection; 14. Going wide, going deep; IV. Models in question: 15. Justifying models; 16. Evaluating models; 17. Final words; V. Appendices: 18. Causal Queries; 19. Glossary; Bibliography; Index.

Macartan Humphreys is Professor of Political Science at Columbia University and Director of the Institutions and Political Inequality group at the WZB Berlin, conducting research on post-conflict development, ethnic politics, and democratic decision-making. He has been President of the APSA Experimental Political Science section and Executive Director of the Evidence on Governance and Politics network. Alan M. Jacobs is Professor of Political Science at the University of British Columbia, conducting research on comparative political economy in democratic settings. He has been President of the APSA's Qualitative and Multi-Method Research section, winner of the section's Mid-Career Achievement Award, and a regular instructor at the Institute for Qualitative and Multi-Method Research.

Reviews for Integrated Inferences: Causal Models for Qualitative and Mixed-Method Research

'An ambitious attempt to understand and test qualitative theories in social science by embedding their design and analysis into a quantitative Bayesian framework, this book will give economists, political scientists, and other researchers a lot to chew on for years to come.' Andrew Gelman, Professor of Statistics and Political Science, Columbia University