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Published on: January 8, 2020
From Disparate Lists to Population Estimates: A Multiple Systems Estimation Workflow for Mortality Analysis in
1Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Demography
|August 13, 2026
Summary
Nontraditional data sources offer insights into conflict mortality. Modeling approaches can address missing data, potentially changing conclusions about mortality in conflict zones.
Area of Science:
- Epidemiology
- Conflict Studies
- Data Science
Background:
- Mortality data in conflict settings are often incomplete.
- Nontraditional data sources present unique challenges and opportunities for analysis.
- Addressing missing data is crucial for accurate interpretation.
Purpose of the Study:
- To explore the utility of nontraditional data sources for conflict mortality.
- To demonstrate how modeling approaches can handle missing data.
- To assess the impact of data correction on mortality conclusions.
Main Methods:
- Utilized nontraditional data sources.
- Applied statistical modeling techniques to address missing data.
- Compared results before and after data correction.
Main Results:
- Nontraditional data sources provide valuable insights into conflict mortality.
- Modeling approaches effectively addressed missing data challenges.
- Correcting missing data altered substantive conclusions regarding mortality.
Conclusions:
- Nontraditional data and modeling are essential for understanding conflict mortality.
- Methodologies for handling missing data are adaptable to various research areas.
- Accurate data handling is critical for reliable research findings.
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