Comparative Hypothesis Testing Via Process Tracing

By I. Rohlfing. 2014

74 citations recorded by the source corpus.

Causal inference via process tracing has received increasing attention during recent years. A 2 × 2 typology of hypothesis tests takes a central place in this debate. A discussion of the typology demonstrates that its role for causal inference can be improved further in three respects. First, the aim of this article is to formulate case selection principles for each of the four tests. Second, in focusing on the dimension of uniqueness of the 2 × 2 typology, I show that it is important to distinguish between theoretical and empirical uniqueness when choosing cases and generating inferences via process tracing. Third, I demonstrate that the standard reading of the so-called doubly decisive test is misleading. It conflates unique implications of a hypothesis with contradictory implications between one hypothesis and another. In order to remedy the current ambiguity of the dimension of uniqueness, I propose an expanded typology of hypothesis tests that is constituted by three dimensions.

Subfields: Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9616542fefb59da58728a33eb96705b9592aacb5

Citations in the corpus

• Process Tracing and Contribution Analysis: A Combined Approach to Generative Causal Inference for Impact Evaluation (2014, unknown): “As our knowledge about the relevant causal factors at this stage is still relatively poor, we start from a test where confirmation of one causal mechanism does not automatically eliminate others (i.e. where causal mechanisms are not mutually-exclusive, Rohlfing 2013).”