Ingo Rohlfing

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)](http://dx.doi.org/10.1177/0049124109339369){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}. 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](https://ingorohlfing.wordpress.com/2014/07/16/what-is-qca-simple-question-many-answers/){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}. I conceive of CNA as an
alternative to the Quine-McCluskey (QMC) algorithm that Ragin chose as
the default algorithm for QCA in his foundational book in 1987.

Baumgartner describes CNA in formal terms in various publications and I
do not need to go into its details here ([[here the probably most
accessible
discussion](http://dx.doi.org/10.1177/1525822X12462527){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}). In (very) short, the
argument is that a term -- a single condition, a conjunction, or a
disjunction -- is causally related to the outcome when no proper part
(superset) of the term is also related to the outcome. ABC is causal for
Y when neither AB, AC, BC, A, B nor C are tied to the outcome. A, B and
C are non-redundant conjuncts of ABC and the absence of any of these
conjuncts is associated with the absence of the outcome.

In addition to the nature of the algorithm, CNA differs from QMC in two
important ways. First, it dispenses with the counterfactuals that are
essential for deriving the intermediate and parsimonious solution with
QMC. [[As Baumgartner
explains](http://dx.doi.org/10.1007/s11135-014-0026-7){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}, this allows one to avoid
untenable counterfactuals about issues such as female African American
presidents of the United States or pregnant men. Second and relatedly,
CNA produces only one solution that is identical with the parsimonious
solution and that [[Baumgartner argues as being the only solution that
is causally
interpretable](http://dx.doi.org/10.1007/s11135-014-0026-7){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"} (an argument with which I
disagree, but that is a topic for another blog post).

What is probably less well-understood among QCA researchers is that the
algorithm is anchored in a regularity theory of causation. This can be
inferred from Baumgartner's discussions of CNA and because he [[anchors
the algorithm in a regularity
theory](http://dx.doi.org/10.1007/s10670-013-9438-3){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"} drawing on Mackie's INUS
theory of causation which is, in turn, a regularity theory of causation
that further develops Hume's widely known theory of causation as
constant conjunction.

I belong to the group of probably not so many people in the social
sciences who do not have fundamental problems with regularity theories
that receive favorable treatment, neither in the quantitative literature
nor in the qualitative literature (I would say much less in [[the
qualitative literature that pits mechanisms and process tracing against
regularity
theories](https://books.google.de/books?id=5iulb1MInPcC&printsec=frontcover&dq=beach+pedersen+process&hl=de&sa=X&redir_esc=y#v=onepage&q=cell%204%20in%20table%203.1&f=false){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}). Since it is always important
to understand what the theory of causation is on which our methods are
built, it is worth emphasizing that you buy in a regularity theory when
you do CNA.

This is not bad *per se*, but one should know it and I doubt that
everyone who referenced Mackie meant it to be a reference to his
regularity theory as opposed to merely referring to the idea of INUS
causes. In this sense, I disagree with Baumgartner who, for example,
cites [[Mahoney and
Goertz](http://dx.doi.org/10.1093/pan/mpj017){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"} as subscribers to Mackie's
theory because they also favor an "asymmetric approach to causation"
(chap. 5 in the [[A Tale of Two
Cultures](http://www.amazon.com/gp/product/0691149712?keywords=a%20tale%20of%20two%20cultures&qid=1449602844&ref_=sr_1_1&s=books&sr=1-1#reader_0691149712){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"} book) that does not fit with
Mackie.

In addition, QCA researchers should note that regularity theories relate
types to each other. [[As Baumgartner
notes](http://dx.doi.org/10.1007/s11406-007-9114-4){style="color:#3366ff;"
target="_blank"}]{style="color:#3366ff;"}, they can hardly handle the
causal analysis of singular cases (not the same as single cases) that
are characterized by specific features related to place and time, for
example. This challenges, in my reading, the idea of QCA as case-based
method that also takes singular features of cases into account in the
case-based part. As a regularity theorist of causation, this is not an
issue for Baumgartner, but this is relevant for empirical QCA
researchers who like the idea of QCA as a case-based method and do not
want to conceive of singular cases as instantiations of regularities.
This shows that the exciting invention of CNA as an alternative
algorithm to QMC has implications that stretch beyond the truth table
analysis for which algorithms are devised.


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.

Publicaciones de Rogue Scholar

You are a regularity theorist when using the Coincidence Analysis algorithm in QCA