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Bayesian Adaptive Approach to Estimating Sample Sizes for Seizures of Illicit Drugs

NCJ Number
239620
Journal
Journal of Forensic Sciences Volume: 57 Issue: 1 Dated: January 2012 Pages: 80-85
Author(s)
Rossana Moroni, Ph.D.; Laura Aalberg, Ph.D.; Tapani Reinikainen, Ph.D.; Jukka Corander, Ph.D.
Date Published
January 2012
Length
6 pages
Annotation
This article discusses the forensic practices in estimating an adequate size for a subset of units from a police seizure containing illicit drugs.
Abstract
A considerable amount of discussion can be found in the forensics literature about the issue of using statistical sampling to obtain for chemical analyses an appropriate subset of units from a police seizure suspected to contain illicit material. Use of the Bayesian paradigm has been suggested as the most suitable statistical approach to solving the question of how large a sample needs to be to ensure legally and practically acceptable purposes. Here, the authors introduce a hypergeometric sampling model combined with a specific prior distribution for the homogeneity of the seizure, where a parameter for the analyst's expectation of homogeneity (x) is included. The results show how an adaptive approach to sampling can minimize the practical efforts needed in the laboratory analyses, as the model allows the scientist to decide sequentially how to proceed, while maintaining a sufficiently high confidence in the conclusions. Published by arrangement with John Wiley & Sons.