ScholarGate
Assistent
Regression modelSpatial methods for conflict

Spatial Conflict Analysis

Spatial conflict analysis models armed conflict while taking geography seriously: conflict is not randomly scattered but clusters in space, and a place's risk depends on its neighbors. Building on georeferenced data and spatial-statistical methods — as in Ward and Gleditsch's (2002) MCMC approach to the spatial context of war and peace — it uses spatial weights, tests for spatial autocorrelation, and fits spatial regression models so that conflict, peace, and their predictors are analyzed as interdependent across locations rather than as isolated observations.

Åbn i MethodMindSnartAnvend, sammenlign, få vejledning
Værktøjer og ressourcer
Hent slides
Lær og udforsk
VideoSnart

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Metodekort

Nabolaget af beslægtede metoder — vælg en knude for at udforske.

Kilder

  1. Ward, M. D., & Gleditsch, K. S. (2002). Location, location, location: An MCMC approach to modeling the spatial context of war and peace. Political Analysis, 10(3), 244–260. DOI: 10.1093/pan/10.3.244

Sådan citerer du denne side

ScholarGate. (2026, June 22). Spatial Analysis and Modeling of Armed Conflict. ScholarGate. https://scholargate.app/da/international-relations/spatial-conflict-analysis

Hvilken metode?

Stil denne metode ved siden af dens nærmeste slægtninge, og læs dem side om side — biblioteket lægger bøgerne på bordet; valget er dit.

Sammenlign side om side

Refereret af

ScholarGateSpatial Conflict Analysis (Spatial Analysis and Modeling of Armed Conflict). Hentet 2026-06-24 fra https://scholargate.app/da/international-relations/spatial-conflict-analysis · Datasæt: https://doi.org/10.5281/zenodo.20539026