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Category: Comparative research and configurational methods

Intuitions about case selection are often wrong

Published by demetriodor on September 5, 2017

Imagine the following simple setup: there are two switches (X and Z) and a lamp (Y). Both switches and the lamp are ‘On’. You want to know what switch X does, but you have only one try to manipulate the switches. Which one would you choose to switch off: X, Z or it doesn’t matter? These are the results of the quick Twitter poll I did on the question: Two switches X and Z control lamp Z. Both switches & the lamp are On. You wanna learn what X does. You have one try. Which switch to press? — Dimiter Toshkov (@DToshkov) September 4, 2017 Clearly, almost half of the respondents think it doesn’t matter, switching X is the second choice, and only 2 out of 15 would switch Z to learn what X does. Yet, it is by pressing Z that we have the best chance of learning something about the effect of X. This seems quite counter-intuitive, so let me explain. First, let’s clarify the assumptions embedded in the setup: (A1) both switches and the lamp can be either ‘On’ [1 ] or ‘Off’ [0]; (A2) the lamp is controlled only by these switches; there is nothing outside the system that controls its output; (A3) X and Z can work individually or in combination (so that the lamp is ‘On’ only if both switches are ‘On’ simultaneously). Now let’s represent the information we have in a table: Switch X Switch Z Lamp Y 1 1 1 0 0 0 We are…

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More on QCA solution types and causal analysis

Published by demetriodor on September 4, 2017

Following up my post on QCA solution types and their appropriateness for causal analysis, Eva Thomann was kind enough to provide a reply. I am posting it here in its entirety : Why I still don’t prefer parsimonious solutions (Eva Thomann) Thank you very much, Dimiter, for issuing this blog debate and inviting me to reply. In your blog post, you outline why, absent counterevidence, you find it justified to reject applied Qualitative Comparative Analysis (QCA) paper submission that do not use the parsimonious solution. I think I agree with some but not all of your points. Let me start by clarifying a few things. Point of clarification 1: COMPASSS statement is about bad reviewer practice It´s good to see that we all seem to agree that “no single criterion in isolation should be used to reject manuscripts during anonymous peer review”. The reviewer practice addressed in the COMPASSS statement is a bad practice. Highlighting this bad reviewer practice is the sole purpose of this statement. Conversely, the COMPASSS statement does not take sides when it comes to preferring specific solution types over others. The statement also does not imply anything about the frequency of this reviewer practice – this part of your post is pure speculation.  Personally I have heard people complaining about getting papers rejected for promoting or using conservative (QCA-CS), intermediate (QCA-IS) and parsimonious solutions (QCA-PS) with about the same frequency. But it is of course impossible for COMPASSS to get a representative picture of this phenomenon. The…

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QCA solution types and causal analysis

Published by demetriodor on August 25, 2017

Qualitative Comparative Analysis (QCA) is a relative young research methodology that has been frequently under attack from all corners, often for the wrong reasons. But there is a significant controversy brewing up within the community of people using  set-theoretic methods (of which QCA is one example) as well. Recently, COMPASSS – a prominent network of scholars interested in QCA – issued a Statement on Rejecting Article Submissions because of QCA Solution Type. In this statement they ‘express the concern … about the practice of some anonymous reviewers to reject manuscripts during peer review for the sole, or primary, reason that the given study chooses one solution type over another’. The ‘solution type’ refers to the procedure used to minimize the ‘truth tables’ which collect the empirical data in QCA (and other set-theoretic) research when there are unobserved combinations of conditions (factors, variables) in the data. Essentially, in cases of missing data (which is practically always) together with the data minimization algorithm the solution type determines the inference you get from the data. I have not been involved in drawing up the statement (and I am not a member of COMPASSS), and I have not reviewed any articles using QCA recently, so I am not directly involved in this controversy on either side. At the same time, I have been interested in QCA and related methodologies for a while now, I have covered their basics in my textbook on research design, and I remain intrigued both by their promise and their…

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