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Activity Number: 110 - Data Science for the Public Good
Type: Invited
Date/Time: Monday, August 3, 2020 : 1:00 PM to 2:50 PM
Sponsor: Caucus for Women in Statistics
Abstract #309566
Title: Statistical Challenges in Casualty Estimation
Author(s): Kristian Lum*
Companies: HRDAG
Keywords: capture-recapture; record linkage; population estimation
Abstract:

An accurate understanding of the magnitude and dynamics of casualties during a conflict is important for a variety of reasons, including historical memory, retrospective policy analysis, and assigning culpability for human rights violations. However, during times of conflict and their aftermath, collecting a complete or representative sample of casualties can be difficult if not impossible. One solution is to apply population estimation methods-- sometimes called capture-recapture or multiple systems estimation-- to multiple incomplete lists of casualties to estimate the number of deaths not recorded on any of the lists. In this talk, I give an introduction to the procedures by which population estimation is performed in the context of conflict mortality, which mainly consists of a record linkage step followed by capture-recapture estimation. I then describe some of my recent work in this area, which is directed at elucidating the limitations of these statistical methods and proposing variants with better properties. I will conclude with a discussion of open questions in this challenging area of applied statistics.


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