Integrated Inferences: Causal Models for Qualitative and Mixed-Method Research
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Book Overview
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.
Format:Paperback
Language:English
ISBN:1316620662
ISBN13:9781316620663
Release Date:November 2023
Publisher:Cambridge University Press
Length:300 Pages
Weight:1.52 lbs.
Dimensions:0.9" x 6.7" x 9.6"
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