Scholars are interested in not just what event happens but also when the event happens. If there is dependence among events or dependence between time and events, however, the currently common methods (e.g., competing risks approaches) produce biased estimates. To deal with these problems, this article proposes a new method of copula-based ordered event history analysis (COEHA). A merit of working with copulas is that, whatever marginal distributions time and event variables follow (including the Cox model), researchers can derive whatever joint distribution exists between the two. Application of the COEHA model to a dataset from civil wars supports two controversial hypotheses. First, as wars become longer, rebel victory becomes more likely but settlement does not (there is dependence between time and events at both tails). Second, stronger rebels make wars shorter but do not necessarily tend to win, as experts predict but fail to establish (rebels’ strength shortens time but has no effect on which events occur). Supplementary materials for this article are available online.
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