Inspired by an email exchange I had with someone on theoretically non-exclusive hypotheses in Bayesian process tracing, I believed it might be useful to write down some thoughts in a blog post. It ended up as a PDF on Github because it has a minor R element and formal notation.

Review of the first chapter of the book “Multi-Method Social Science” by Jason Seawright, published with Cambridge University Press in 2016.

The idea of most-likely and least-likely cases dates back to Eckstein and was one of the few remaining things in qualitative research there seemed to be no disagreement about because they are considered an asset in causal analysis. In a paper that is advance access, Beach and Pedersen (BP) now argue that process tracing and the analysis of mechanisms does not make sense with most-likely and least-likely cases.

Most multi-method research (MMR) studies with which I am familiar start with regression analysis (or, in recent years, QCA) and perform the case studies afterward. This is the order recommended by Lieberman in his nested analysis article which, in turn, most probably reflects the widely held view that case studies are only worth doing in MMR when something is going on at the cross-case level.

More often than one might expect, television series and films offer excellent illustrations of methodological and methods-related arguments (which is worth a blog post of its own). When I was working on my paper on comparative hypothesis testing in process tracing, I was watching the first season of the terrific TV series, Homeland.

People familiar with the development of qualitative methods know that process tracing has developed rapidly over the last years. As the discussion about a method becomes broader and deeper, it becomes more important to systematize and sort the field in order to understand what it can and cannot achieve.

The choice of cases for empirical analysis is a central topic in the methods literature. The argument that quantitative and qualitative research studies different templates, which is probably most forcefully described in A Tale of Two Cultures , does not come as a surprise. What I want to focus on here are the arguments on case selection in qualitative research.

The methods literature on process tracing took a Bayesian turn in recent years. Bayesian inference, whereby you condition on evidence in order to update your prior confidence in a hypothesis, is presented as a mode of inference one should follow in process tracing (Bennett, Andrew (2008): Process-Tracing: A Bayesian Perspective. Box-Steffensmeier, Janet M., Henry Brady and David Collier (ed.):

Qualitative Methods (i.e., process tracing, set theoretic methods, informal Bayesian inference etc.) and multi-method research, in particular the combination of regression analysis or QCA with case studies, are certainly a growth industry in political science and sociology. In light of some methods panels held at the APSA Annual Meeting in Chicago and the ECPR General Conference in Bordeaux, this might actually come as a surprise.

In the case study literature, one new pair of terms has been established by the field that concerns the distinction between data set observations and causal process observations . In short, Collier, Brady, and Seawright (2004: Sources of Leverage in Causal Inference: Toward an Alternative View of Methodology. Brady, Henry E. and David Collier (eds.): Rethinking Social Inquiry.