Reflecting the rising popularity of research that combines
qualitative and quantitative social science, Multi-Method Social
Science provides the first systematic guide to designing
multi-method research. It argues that methods can be productively
combined using the framework of integrative multi-method research,
with one method used to carry out a final causal inference, and
methods from other traditions used to test the key assumptions
involved in that causal inference. In making this argument, Jason
Seawright considers a wide range of statistical tools including
regression, matching, and natural experiments. The book also
discusses qualitative tools including process tracing, the use of
causal process observations, and comparative case study research.
Along the way, the text develops over a dozen multi-method designs
to test key assumptions about social science causation.
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