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Building on Solid Ground: Robust Case Selection in Multi‐Method Research
Author(s) -
Rohlfing Ingo,
Starke Peter
Publication year - 2013
Publication title -
swiss political science review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.632
H-Index - 30
eISSN - 1662-6370
pISSN - 1424-7755
DOI - 10.1111/spsr.12052
Subject(s) - causal inference , process tracing , selection (genetic algorithm) , computer science , inference , econometrics , process (computing) , intersection (aeronautics) , focus (optics) , empirical research , regression , management science , operations research , machine learning , artificial intelligence , political science , economics , mathematics , statistics , politics , engineering , law , physics , optics , aerospace engineering , operating system
The social sciences are currently witnessing a trend toward multi‐method research ( MMR ). However, many important issues have not been sufficiently addressed so far. The focus of this paper is case selection for process tracing on the basis of regression results, which is the main point of intersection between the two methods. Based on a review, we first show that the current empirical and methodological literature does not fully appreciate the implications of modeling uncertainty and non‐robust quantitative results. The major problem is that non‐robust regression results may lead to invalid choices and faulty inferences. We develop a novel selection procedure that takes these issues into account and improves causal inference in MMR .