Statistics vs machine learning: an application on time-to-event data in terrorist kidnapping events
DOI:
https://doi.org/10.71014/sieds.v80i2.429Abstract
Hostage-taking durations in terrorist attacks using the Global Terrorism Database have been considered in this paper using data from 1970 to 2021. Employing conditional inference trees and Cox proportional hazards models, we managed to determine factors influencing hostage release time. Attack type and ransom demands significantly prolong incident duration, with effects varying over time. Regional variations have also been detected, with Middle East & North Africa and Southeast Asia showing longer median durations. The complementary insights from machine learning providing a clustering of individuals based on survival time and statistical methodologies which provide a clustering of the effects of the covariates on the instantaneous risk of surviving yield a robust framework for understanding complex events such as kidnapping.
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