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Annoucements > Conferences

Conferences, Workshops and Seminars

This is a non-exhaustive list of the forthcoming and past meetings about QCA broadly speaking (but not sponsored by COMPASSS). This includes workshops, conference panels and sessions, colloquiums, etc… If you have any suggestion or comment concerning this page, please send an email to Damien Bol

Forthcoming meetings:

2 - 4 September 2010, Eötvös Lorànd University of Budapest, Hungary

8th ESPAnet Conference

STREAM ON COMPARATIVE METHODOLOGY

The stream on comparative methodology is happy to welcome papers using fsQCA or related techniques

Social policy researchers routinely make complex decisions about how to design their comparative studies. The big five questions for the comparative researcher are: How many and which cases should be included? How should the cases or observations be conceived and what are the key concepts? How can counterfactuals be utilized and their usage evaluated? Which indicators provide measures on these concepts that can be compared across time and space? How can different methodologies help best address the issue in question? Despite the important implications that comparative social policy researchers’ decisions on these issues have for the findings of their analysis, it is rare that scholars at length discuss the challenges they face, the choices they make and the implications these choices have for research and policy recommendations. The purpose of this stream is to present and discuss the choices social policy researchers have to make in comparative research and in particular how to improve the state of the art.

In this stream we therefore invite papers that pay explicit attention to the methodological challenges and decisions that concern case selection, concept formation, the role of counterfactuals, establishing of measurement validity, and multi-method design. We welcome papers that address one or more of these key issues. We encourage papers to apply new approaches in comparative social policy and through such applications demonstrate the strength and weaknesses of the new approaches. We do not invite literature reviews, theoretical papers, and papers already accepted for publication. Innovative papers discussing or applying new approaches are prioritized.

Abstracts answering this call for papers should preferably make clear what the paper is about, what the contribution is, and how the contribution is made, and be submitted before March 29

Convenors:

• Patrick Emmenegger (University of Southern Denmark)
• Olli Kangas (University of Helsinki)

For more information, click HERE

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May 2011

Methodological Innovations Online

SPECIAL ISSUE - CALL FOR PAPERS

Methodological Innovations Online will publish a special issue in May 2011 entitled Case-Based Approaches to the Analysis of Quantitative Data.

Within the social sciences generally, the conventional approach to the analysis of survey data remains variable-based, employing some member of the regression family. Regression methods address the effect of one or more supposedly “independent” variables on some outcome. Individual cases, the carriers of the variables, usually remain in the background, as do, often, underlying causal mechanisms and processes. It is variables that act, having their effects on a dependent outcome variable. In the typical multivariate study, the purpose is to report the net (and often average) effect of each independent variable. The underlying mathematics is matrix algebra and the typical model additive. Causal homogeneity, usually, is assumed across cases (an assumption whose realism was questioned by Ralph Turner as long ago as 1948). Over the past 30 years, a number of authors have published important critiques - sometimes unjustly neglected - of the assumptions of this form of variable analysis. Abbott, Byrne, Freedman, Lieberson, Pawson and Ragin, amongst others, have contributed much to our understanding of its limitations. A key assumption of the default model is that “independent” variables do indeed act independently of one another. As Ragin (2006) argues, in this “net effects” approach, "estimates of the effects of independent variables are based on the assumption that each variable, by itself, is capable of producing or influencing the level or probability of the outcome. While it is common to treat "causal" and "independent" as synonymous modifiers of the word "variable," the core meaning of "independent" is this notion of autonomous capacity. Specifically, each independent variable is assumed to be capable of influencing the level or probability of the outcome regardless of the values or levels of other variables (i.e., regardless of the varied contexts defined by these variables)" (14-15).

Ragin has developed one approach, Qualitative Comparative Analysis (QCA), based in set theory, which allows us to move away from this assumption. QCA is designed to address conjunctural causation; it allows a researcher rigorously to model processes whose outcomes are the result of the combined effect of several factors. QCA addresses relations of causal sufficiency and necessity rather than linear additive causation. In the application of this holistic approach to large scale survey data the case, rather than disappearing from sight, is retained, existing as a configuration of conjoined factors (see, e.g. Ragin, 2006, Cooper, 2005). Others approaches such as cluster analysis, correspondence analysis and sequence analysis also offer fruitful ways forward (Byrne & Ragin, 2009).

Methodological Innovations Online will publish in May 2011 a special issue addressing the application of broadly case-based approaches, such as those mentioned above, to quantitative data. Submissions of methodological and substantive papers addressing this topic should be made to the editors, by email, by the 30th September 2010, to the guest editors:

• Barry Cooper (University of Durham)
• Judith Glaesser (University of Durham)

For further details, click HERE

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