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Measuring Elusive Populations with Bayesian Model Averaging for Multiple Systems Estimation: A Case Study on Lethal Violations in Casanare, 1998-2007

Collecting data for the analysis of past human rights violations is fraught with challenges. For example, individuals from or about whom data should be collected may be displaced, missing, or dead. Some reports of acts may be easier to find than others, and as a result, datasets will be biased toward those cases. These challenges must be overcome in order to create effective official policy for violence mitigation and prevention. This relies on statistical analyses that can meet these challenges. We propose a combination of Bayesian Model Averaging and Multiple Systems Estimation as an example of this type of analysis, which presents an important advancement in human rights research. In particular, this method allows the use of multiple data sources to estimate the number of undocumented violations – those that have not been recorded by any source. We present an application of this method in Casanare, Colombia, where we estimate a total (both documented and undocumented) of 5,832 killings (95% credible interval: 3,822, 9,332) and 2,345 disappearances (1,221, 4,901) between 1998 and 2007.