Empirical validation of a family-member prioritization approach to maximize statistical power in missing person cases

In order to prioritize the exhumation of the most informative reference relatives to increase the statistical power of a reference group, a conditional simulation approach for missing person identification that combines both exclusion and inclusion power in reference families has been previously developed. The aim of this study is to empirically validate this approach by comparing its predicted theoretical prioritization model with the observed changes in statistical power in real cases of our laboratory, in which new relatives had already been added. We conclude that this approach is a reliable tool to choose the most appropriate reference relatives to complete a family group and improve the identification power of a Missing Person (MP).