We explain and demonstrate how the researcher can identify recurring patterns across cases on the basis of the calibrated data matrix, in a systematic and transparent way. The comparative process in QCA consists of three main steps. First, the calibrated data matrix needs to be transformed into a truth table. In the truth table, the cases are sorted across the logically possible configurations of conditions. Second, the truth table has to be minimized. This is done through the pairwise comparison of truth table rows that are considered to agree on the outcome and differ in their score in but one of the conditions. The result of the minimization is a solution formula. Third, the solution formula needs to be interpreted. Two common issues in the truth table minimization are limited diversity and logical contradictions. We present various strategies for dealing with these issues.
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