Process-tracing can be used both for inductive (theory-generating) and deductive (theory-testing) purposes. In 'theory-testing process tracing,' the goal is to test existing theories and the causal mechanisms assumed therein. On the contrary, 'theory-building process tracing' involves constructing a theory about a causal mechanism that can be applied to a broader population of a particular phenomenon. Once these observable implications are presented, they are then tested empirically to see which of the observable implications can be observed and which cannot. It is also important to test if alternative explanations are present. •
Straw-in-the-wind tests: Failure or passage of this test neither lends strong support for or against the theory. This means that these tests only slightly weaken the rival hypotheses when the tested hypothesis gets proven. For this test, the requirements are neither necessary nor sufficient to prove the causal effects of the hypotheses.; •
Smoking gun tests: Passing a smoking gun test lends strong support for theory, whereas failure does not necessarily lend strong support against the theory. This is called a sufficient condition. The requirements for the smoking gun test are sufficient but not necessary and passing the test significantly weakens rival hypotheses with different expected mechanisms.; A limitation to process-tracing is the problem of
infinite regress. While some influential works by methods scholars have argued that the ability of process-tracing to make causal claims is limited by low
degrees of freedom, methodologists widely reject that the "degrees of freedom" problem applies to research that uses process-tracing, given that qualitative research entails different logics than
quantitative research (where scholars do need to be wary of degrees of freedom). Another important advantage is that process tracing can deal with theoretical pluralism, which means hypotheses or conceptual models have multiple (un)dependent variables and causal relationships. This method of analysis is therefore suitable for understanding inherent complexity (Kay & Baker, 2015). The reason why process-tracing differs from other qualitative research methods is also an advantage. By assigning probabilities to outcomes under specific conditions, scholars can use
Bayesian rules in their process tracing to draw robust conclusions about the causes of outcomes. By using Bayesian probability, it may be possible to make strong causal inferences from a small sliver of data. ==See also==