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Being accurate about accuracy in verbal deception detection
PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accura...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687387/ https://www.ncbi.nlm.nih.gov/pubmed/31393894 http://dx.doi.org/10.1371/journal.pone.0220228 |
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author | Kleinberg, Bennett Arntz, Arnoud Verschuere, Bruno |
author_facet | Kleinberg, Bennett Arntz, Arnoud Verschuere, Bruno |
author_sort | Kleinberg, Bennett |
collection | PubMed |
description | PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accuracy of a method is to find the optimal statistical separation between lies and truths in a single dataset. However, this method lacks safeguards against accuracy overestimation. METHOD & RESULTS: A simulation study and empirical data show that this procedure produces overoptimistic accuracy rates that, especially for small sample size studies typical of this field, yield misleading conclusions up to the point that a non-diagnostic tool can be shown to be a valid one. Cross-validation is an easy remedy to this problem. CONCLUSIONS: We caution psycholegal researchers to be more accurate about accuracy and propose guidelines for calculating and reporting accuracy rates. |
format | Online Article Text |
id | pubmed-6687387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66873872019-08-15 Being accurate about accuracy in verbal deception detection Kleinberg, Bennett Arntz, Arnoud Verschuere, Bruno PLoS One Research Article PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accuracy of a method is to find the optimal statistical separation between lies and truths in a single dataset. However, this method lacks safeguards against accuracy overestimation. METHOD & RESULTS: A simulation study and empirical data show that this procedure produces overoptimistic accuracy rates that, especially for small sample size studies typical of this field, yield misleading conclusions up to the point that a non-diagnostic tool can be shown to be a valid one. Cross-validation is an easy remedy to this problem. CONCLUSIONS: We caution psycholegal researchers to be more accurate about accuracy and propose guidelines for calculating and reporting accuracy rates. Public Library of Science 2019-08-08 /pmc/articles/PMC6687387/ /pubmed/31393894 http://dx.doi.org/10.1371/journal.pone.0220228 Text en © 2019 Kleinberg et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kleinberg, Bennett Arntz, Arnoud Verschuere, Bruno Being accurate about accuracy in verbal deception detection |
title | Being accurate about accuracy in verbal deception detection |
title_full | Being accurate about accuracy in verbal deception detection |
title_fullStr | Being accurate about accuracy in verbal deception detection |
title_full_unstemmed | Being accurate about accuracy in verbal deception detection |
title_short | Being accurate about accuracy in verbal deception detection |
title_sort | being accurate about accuracy in verbal deception detection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687387/ https://www.ncbi.nlm.nih.gov/pubmed/31393894 http://dx.doi.org/10.1371/journal.pone.0220228 |
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