方法对比

	Conflict Diffusion Analysis	Dyadic Conflict Analysis
领域	International Relations	International Relations
方法族	Regression model	Process / pipeline
起源年份	2008	1992
提出者	Conflict-diffusion literature (e.g., Most & Starr; Halvard Buhaug & Kristian Skrede Gleditsch)	Stuart A. Bremer (and the Correlates of War dyadic tradition)
类型	Spatial-temporal analysis of conflict contagion	Observational research design for interstate conflict
开创性文献	Buhaug, H., & Gleditsch, K. S. (2008). Contagion or confusion? Why conflicts cluster in space. International Studies Quarterly, 52(2), 215–233.	Bremer, S. A. (1992). Dangerous dyads: Conditions affecting the likelihood of interstate war, 1816–1965. Journal of Conflict Resolution, 36(2), 309–341.
别名	Conflict Contagion Analysis, Conflict Spillover Analysis, Spatial Diffusion of War, Conflict Spread Modeling	Dyad-Year Analysis, Dyadic Design in Conflict Studies, Dangerous Dyads Analysis, Pairwise Interstate Conflict Analysis
相关	3	3
摘要	Conflict diffusion analysis studies how conflict spreads from one place to another — across borders, between neighboring regions, over time. It addresses a sharp inferential challenge posed by Buhaug and Gleditsch (2008): conflicts cluster in space, but clustering can reflect either genuine contagion (a war next door actually raises your risk) or merely the fact that neighbors share war-prone conditions. Using spatial-temporal lags of neighboring conflict alongside covariates, and theorizing concrete transmission mechanisms such as refugee flows and transnational ethnic ties, the method tries to separate true diffusion from spurious co-location.	Dyadic conflict analysis is the dominant research design in quantitative conflict studies: it treats the pair of states (the dyad), observed year by year, as the unit of analysis and models the probability that a pair experiences militarized conflict as a function of their joint and individual attributes. Stuart Bremer's 'Dangerous Dyads' (1992) is the canonical statement, identifying which conditions — contiguity, the absence of alliance, power parity, the absence of joint democracy, and others — make a pair of states war-prone. The design aligns conflict data with the relational theories that dominate the field.