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.

One of the recent big and, in my view, underappreciated innovations in the field of Qualitative Comparative Analysis (QCA) is Baumgartner’s formulation of the Coincidence Analysis algorithm (CNA). Baumgartner presents it as an alternative to QCA, which I do not find convincing because I do not see QCA married to a specific algorithm.

For what it’s worth, I wanted to see how often ‘process tracing’ is mentioned in the offerings on Google Books.

For some time now, a discussion has been raging about the pros and cons of set theory and the use of set-theoretic methods (STM) in the social sciences (e.g., in Sociological Methodology and the APSA Newsletter). Following up on a critical discussion by Paine and a constructive, comparative discussion of STM and regression analysis by Thiem, Baumgartner and Bol (TBB), Comparative Political Studies organized a symposium on STM.

In Finding Pathways: Mixed-Method Research for Studying Causal Mechanisms , Weller and Barnes seek to explain “how the small-N component of multi-method research can meaningfully contribute and add value to the study of causal mechanisms” (quote from blurb). The book contains nine chapters, including the introduction and concluding chapter.

Let’s imagine you are attending a presentation and the presenter does not follow the standard intro-literature-theory-design-results-conclusion structure. Instead, she only presents the results of her research. What would be the first question you would ask? I assume at least 90 percent of the audience would ask about how she arrived at her findings.

Among the recent criticisms of QCA, Lucas and Szatrowski’s (LS) critique stands out in multiple respects, including its scope, its tone (QCA is “a nonanalytic means to identify asymmetric causal illusions”, p. 66), and the responses it provoked (and the notorious mistake in their first simulation). Naturally, the critical replies focused on LS’s assessment of QCA, but I find that they make an almost equally interesting and ironic claim at the

How to enhance reproducibility when using fs/QCA software

Recently, I came across an interesting study from 2009, the content of which is not relevant here.

As is well known, QCA has been under intense scrutiny in recent years and subject to criticism (sometimes quite strong). I am not going to review studies on the validity of QCA that entail criticism;