Congruence Analysis

Epistemological Relativism and Theoretical Pluralism

Practitioners of congruence analysis indicate that empirical findings are strongly influenced by the theoretical lenses employed. Therefore, congruence analysis has a clear affinity for relativist epistemologies, which results in the conviction that empirical research cannot be used to verify or falsify theories but just to provide evidence for the relative strength of a theory by providing understandings and explanations. Congruence analysis is compatible with a broad epistemological spectrum, from radical epistemological constructivism, which accepts no external reality but uses empirical observations as material to demonstrate the power of a theory to create meaningful interpretations, to positivism, which perceive theories as more or less powerful instruments to shed light on an objectively existing reality. A possible consequence for all of these epistemological starting points is to apply a plurality of theoretical lenses in studying empirical cases. This [Page 211]plurality of theoretical lenses will provide a more comprehensive understanding and/or explanation of a specific case.

“Prediction” More Broadly Understood

Congruence analysis differs from congruence method on the basis of a broader meaning of “predictions.” In congruence analysis, predictions are not limited to the expected covariation between dependent and independent variables. Instead, the predictions derived from theory should be as diverse as possible and should include not only data-set observations (values of independent and dependent variables) and causal process observations (e.g., sequences of events) but also predictions about the most important actors, their perceptions, and their motivations (traces of micro-foundational causal mechanisms) or other fundamental elements of the theory. In order to be able to deduce these kinds of predictions, theories must be conceptually rich. They must go beyond a hypothesis, which just predicts a specific causal relationship between a factor and an outcome.

We can distinguish among three different approaches in respect to the question of how to weight the various predictions/observations when the researcher draws conclusions for the theories from the (non)congruence of predictions and empirical observations. A quantitative approach would count and weigh every match and every mismatch between prediction and observation equally. More qualitatively oriented scholars would argue that some predictions are more important than others. Those who lean toward a positivist understanding of congruence analysis would point to the predicted covariation between dependent and independent variables. It seems, however, that the most consistent approach within congruence analysis would be to give most importance to the conceptual core of a theoretical approach rather than the necessary outcome, given specific values of the causal factors.

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