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Hazard Rate

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...

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Quantifying the future lethality of terror organizations.

Yang Yang^1,2, Adam R Pah^1,2, Brian Uzzi^3,2

¹Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208.

Proceedings of the National Academy of Sciences of the United States of America

|October 9, 2019

Summary

Predicting terrorist group lethality is challenging due to concealed data. This study introduces a statistical model using latent variables to estimate future violence, providing an early warning signal from initial attacks.

Keywords:

counter-terrorism human conflict organizational behavior statistical models terrorism

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Area of Science:

Computational social science
Political science
Statistics

Background:

Terrorist groups are increasingly sophisticated, posing significant international security challenges.
Predicting insurgent violence is crucial but hindered by concealed group capabilities and resources.

Purpose of the Study:

To develop a statistical model for estimating a terrorist group's future lethality.
To infer intrinsic group capabilities and resources using latent-variable modeling.

Main Methods:

Latent-variable modeling to infer concealed group attributes.
Introduction of two novel explanatory variables for lethality prediction.
Analysis based on early-stage group behavior (first 10-20 attacks).

Main Results:

The model successfully estimates future lethality, explaining approximately 60% of the variance.
The introduced explanatory variables significantly improve prediction accuracy over existing models.
A unique early-warning signal for future lethality is generated from minimal initial attack data.

Conclusions:

The developed model offers a robust method for assessing future terrorist group threats.
Findings have theoretical and practical implications for understanding and mitigating human conflict.
The model provides valuable insights for intelligence agencies and policymakers.