Mixing Methods: A Bayesian Approach

@article{Humphreys2015MixingMA,
  title={Mixing Methods: A Bayesian Approach},
  author={Macartan Humphreys and Alan M. Jacobs},
  journal={American Political Science Review},
  year={2015},
  volume={109},
  pages={653 - 673}
}
We develop an approach to multimethod research that generates joint learning from quantitative and qualitative evidence. The framework—Bayesian integration of quantitative and qualitative data (BIQQ)—allows researchers to draw causal inferences from combinations of correlational (cross-case) and process-level (within-case) observations, given prior beliefs about causal effects, assignment propensities, and the informativeness of different kinds of causal-process evidence. In addition to… 
View on Cambridge Press
columbia.edu
98 Citations
Highly Influential Citations
3
Background Citations
19
Methods Citations
17

98 Citations

Citation Type

Citation Type

Updating Bayesian(s): A Critical Evaluation of Bayesian Process Tracing
Given the increasing quantity and impressive placement of work on Bayesian process tracing, this approach has quickly become a frontier of qualitative research methods. Moreover, it has dominated the…
Explicit Bayesian Analysis for Process Tracing: Guidelines, Opportunities, and Caveats
TLDR
This paper provides step-by-step guidelines for explicit Bayesian process tracing, calling attention to technical points that have been overlooked or inadequately addressed, and illustrates how to apply this approach with the first systematic application to a case study that draws on multiple pieces of detailed evidence.
Applying Formal Bayesian Analysis to Qualitative Case Research: An Empirical Example, Implications, and Caveats
To illustrate how Bayesian logic underpins qualitative research, we provide an application to Fairfield’s (2015) work on tax policy change in Latin America. Fairfield (2013) elaborated a…
A Set-Theoretic Approach to Bayesian Process Tracing
TLDR
The article shows that Bayesian process tracing and set-theoretic process tracing are not alternatives to each other but rather two sides of the same coin.
A Dialogue with the Data: The Bayesian Foundations of Iterative Research in Qualitative Social Science
TLDR
It is argued that mechanisms for distinguishing exploratory from confirmatory stages of analysis that have been suggested in the context of APSA’s DA-RT transparency initiative are unnecessary for qualitative research that is guided by logical Bayesianism.
The Bayesian foundations of iterative research in qualitative social science: a dialogue with the data
TLDR
It is argued that mechanisms for distinguishing exploratory from confirmatory stages of analysis that have been suggested in the context of APSA’s DA-RT transparency initiative are unnecessary for qualitative research that is guided by logical Bayesianism.
Comparative Methods and Process Tracing
TLDR
This report focuses on analytic transparency, leaving transparency in generating and sharing evidence to other QTD reports and differentiates between core recommended practices and emerging practices that might be considered, depending on the costs entailed, by authors, reviewers, and readers.
Mechanisms, Bayesianism, and process tracing
TLDR
The paper shows how the power of process tracing as a qualitative methodology depends on and grows from its set-theoretic underpinnings.
Assessing causal inference problems with Bayesian process tracing: the economic effects of proportional representation and the problem of endogeneity
ABSTRACT In recent years, causal process tracing is becoming increasingly formalised as scholars have begun to follow Bayesian logic and thereby manage to combine the interpretative and contextual…
Qualitative Inference from Causal Models
TLDR
This work describes how Bayesian nets can be used by scholars of process tracing to justify inference strategies with reference to lower level theories and to assess the probative value of new within-case information.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 72 REFERENCES
BAYESIAN INFERENCE FOR COMPARATIVE RESEARCH
RV egression analysis in comparative research suffers from two distinct problems of statistical inference. First, because the data constitute all the available observations from a population,…
Bayesian inference for causal effects in randomized experiments with noncompliance
For most of this century, randomization has been a cornerstone of scientific experimentation, especially when dealing with humans as experimental units. In practice, however, noncompliance is…
Using Qualitative Information to Improve Causal Inference
Using the Rosenbaum (2002, 2009) approach to observational studies, we show how qualitative information can be incorporated into quantitative analyses to improve causal inference in three ways.…
Why Process Matters for Causal Inference
Our goal in this paper is to provide a formal explanation for how within-unit causal process information (i.e., data on posttreatment variables and partial information on posttreatment…
Process Tracing and Causal Inference
How should we judge competing explanatory claims in social science research? How can we make inferences about which alternative explanations are more convincing, in what ways, and to what degree?…
Nested Analysis as a Mixed-Method Strategy for Comparative Research
TLDR
A unified approach which joins intensive case-study analysis with statistical analysis improves the prospects of making valid causal inferences in cross-national and other forms of comparative research by drawing on the distinct strengths of two important approaches.
Process Tracing
Covariations have important limitations as sources of causal inference, whether these covariations are established by statistical methods or by congruence methods in case studies. Because of these…
Quantitative Leverage Through Qualitative Knowledge: Augmenting the Statistical Analysis of Complex Causes
Social scientific theories frequently posit that multiple causal mechanisms may produce the same outcome. Unfortunately, it is not always possible to observe which mechanism was responsible. For…
Process-Tracing Methods: Foundations and Guidelines
TLDR
The authors develop the underlying logic of process-tracing, including how one should understand causal mechanisms and how Bayesian logic enables strong within-case inferences.
Multi-Method Social Science: Combining Qualitative and Quantitative Tools
TLDR
It is argued 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.
...
1
2
3
4
5
...