| Abstract: | This article illustrates the importance of testing empirical models in samples appropriate to the theories the models are intended to test. While social science appears to mandate that we prefer general theories to limited ones, the generality of a theory rests in its logical application to a set of observations, not solely to its statistical survival in a large data set. Theories in international relations, especially those linking domestic turmoil and international conflict, are advancing, but are sometimes applied to samples larger than the related theories indicate. This paper examines the statistical consequences of estimation in overexpansive samples with unmodeled treatment effects; we argue that samples containing cases that cannot experience the causal phenomenon in question produce unmodeled treatment effects, and we reexamine three published articles whose samples are perhaps broader than their theories suggest they should be. The empirical analyses demonstrate that overexpansive samples can produce somewhat misleading results: the new models produce interesting findings that emerge as treatment effects are identified. |
