The Use Of Error Rates To Predict And Characterize The Efficacy Of ...

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Abstract

From a forensic perspective, a presumptive test, one which indicates the presence or absence of a certain target material such as blood, is an invaluable tool. Among these tests, there are different specificities, sensitivities, and shelf lives. The accuracy of a test is an algebraic combination of the specificity and sensitivity of the test. Each test has limitations as given by its false positive and false negative rates. The aim of this study was to illustrate how the false positive and false negative rates are to be properly determined using a simulation study for the phenolphthalein test. New presumptive tests must be properly evaluated/validated through testing of commonly encountered household items and other potentially probative items usually found at crime scenes, however, the makeup of test sets must appropriately capture all error rates. In order to correctly use these results when the test is applied to an unknown sample recovered at a crime scene, the error rates cannot be applied directly to estimate whether or not the sample is actually the analyte of interest. In a validation study, the forensic scientist calculates the false positive rate as the p(Positive Reaction|Blood), whereas at the scene, the crime scene investigator wishes to determine the p(Blood|Positive Reaction). All crime scene investigators need to ensure that the conditional is not transposed when interpreting such results. Furthermore, this work provides a model for the assessment of a multiple test diagnostic system intended for investigators.

Keywords: Bayesian interpretation; error rates; presumptive test; probability; sensitivity; specificity.

© 2021 American Academy of Forensic Sciences.

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References

REFERENCES

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