Maria Cuellar-- Child Abuse on Trial: A Statistical Analysis of Shaken Baby Syndrome

Tuesday, November 1, 2016 - 12:00pm

McNeil 103

Maria Cuellar in a doctoral candidate in Statistics and Public Policy at Carnegie Mellon University. Her research fields include causality in law, statistics in forensic analysis, network sampling, and survey methodology. She is interested in developing survey methodology for hard to reach populations by using network sampling and capture-recapture methodology. She has worked with the Human Rights Data Analysis Group, the Carnegie Mellon Center for Human Rights Science, the CMU National Science Foundation Census Research Network, and the Center for Statistics and Applications in Forensic Evidence. 

Abstract: Over 1,100 individuals are in prison today on charges related to the diagnosis of Shaken Baby Syndrome (SBS). In recent years this diagnosis has come under scrutiny, and more than 20 convictions made on the basis of SBS have been overturned. The overturned convictions have fueled a controversy about alleged cases of SBS. In this talk, I will review the arguments in cases related to SBS and point out two problems: much of the evidence used has contextual bias, as recently defined by the National Commission on Forensic Science, and the expert witnesses and attorneys ask the wrong causal questions. By asking the wrong causal questions, I mean that they ask Effects of Causes questions (e.g. "If a child has these brain injuries, how likely is it that he was shaken?") instead of Causes of Effects questions (e.g. "If this child was shaken and got the triad of injuries, how likely is it that the shaking, and not something else, caused the triad of injuries?"). I suggest that a Causes of Effects framework be used in formulating the causal questions and answers given by attorneys and expert witnesses. I also suggest that only the task-relevant information be provided to the individual who determines the diagnosis. I will close by mentioning my current and future work.