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Exact Bayesian Inference for Assessing the Accuracy of Polygraph Testing

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Abstract

The polygraph test is often used in law enforcement as an investigative tool, and in the courtroom where it is used to bolster support for the innocence of a defendant. The amount of available data to evaluate polygraph accuracy that is taken under realistic conditions is severely limited. With a fully Bayesian approach we analyze the largest such data set that exists. We derive exact results for the posterior distribution of the negative and positive predictive values, which can be evaluated with a computer algebra system. We show that the uncertainties, even given the largest and most realistic data set currently available, are great, casting doubt on the use of polygraph testing in criminal trials.

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Acknowledgements

The author would like to thank the editor and the reviewer for their careful review of the manuscript. Their comments have certainly led to a better paper.

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Authors and Affiliations

  1. Saint Louis University, St. Louis, MO, USA

    Steven E. Rigdon

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  1. Steven E. Rigdon
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Correspondence to Steven E. Rigdon.

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Rigdon, S.E. Exact Bayesian Inference for Assessing the Accuracy of Polygraph Testing. J Indian Soc Probab Stat 19, 67–78 (2018). https://doi.org/10.1007/s41096-018-0034-3

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  • DOI: https://doi.org/10.1007/s41096-018-0034-3

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