Related Experiment Video
Updated: Nov 1, 2025

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
Published on: December 24, 2015
Making decisions in missing person identification cases with low statistical power
Franco L Marsico1, Magnus D Vigeland2, Thore Egeland3
1Banco Nacional de Datos Genéticos, Avda. Córdoba 831, C1054AAH Caba, Argentina.
Abstract:
The present work proposes a general strategy for dealing with missing person identification cases through DNA-database search. Our main example is the identification of abducted children in the last civic-dictatorship of Argentina, known as the "Missing Grandchildren of Argentina". Particularly we focus on those pedigrees where few, or only distant relatives of the missing person are available, resulting in low statistical power. For such complex cases we provide a statistical method for selecting a likelihood ratio (LR) threshold for each pedigree based on error rates. Furthermore, we provide an open-source user friendly software for computing LR thresholds and error rates. The strategy described in the paper could be applied to other large-scale cases of DNA-based identification hampered by low statistical power.
More Related Videos
Related Concept Videos
Decision Making: Traditional Method
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
Detection of Gross Error: The Q Test
Assumptions of Survival Analysis
Mechanistic Models: Compartment Models in Individual and Population Analysis
Errors In Hypothesis Tests

