How Many Samples from a Drug Seizure Need to Be Analyzed?

Coulson, Sally; Coxon, Anne; Buckleton, John

doi:10.1520/jfs15171j

Cited by 14 publications

(10 citation statements)

References 3 publications

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“…The utility of a Bayesian approach in forensic science, including ballistic (Bunch, 2000) and paint matching (McDermott et al, 1999), drug sampling and analysis (Coulson et al, 2001;Goldmann et al, 2004), and DNA identification (Krawczak and Schmidtke, 1992;Evett and Weir, 1998;Thompson et al, 2003;Foreman et al, 1999), is widely known, as it provides the examiner with the likelihood ratio of a positive identification or match that can be presented in court.…”

Section: Osteological Data Likelihood Ratios and Personal Identificmentioning

confidence: 99%

Statistical basis for positive identification in forensic anthropology

Steadman

Adams

Konigsberg

2006

Am. J. Phys. Anthropol.

107

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Forensic scientists are often expected to present the likelihood of DNA identifications in US courts based on comparative population data, yet forensic anthropologists tend not to quantify the strength of an osteological identification. Because forensic anthropologists are trained first and foremost as physical anthropologists, they emphasize estimation problems at the expense of evidentiary problems, but this approach must be reexamined. In this paper, the statistical bases for presenting osteological and dental evidence are outlined, using a forensic case as a motivating example. A brief overview of Bayesian statistics is provided, and methods to calculate likelihood ratios for five aspects of the biological profile are demonstrated. This paper emphasizes the definition of appropriate reference samples and of the "population at large," and points out the conceptual differences between them. Several databases are introduced for both reference information and to characterize the "population at large," and new data are compiled to calculate the frequency of specific characters, such as age or fractures, within the "population at large." Despite small individual likelihood ratios for age, sex, and stature in the case example, the power of this approach is that, assuming each likelihood ratio is independent, the product rule can be applied. In this particular example, it is over three million times more likely to obtain the observed osteological and dental data if the identification is correct than if the identification is incorrect. This likelihood ratio is a convincing statistic that can support the forensic anthropologist's opinion on personal identity in court.

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Section: Osteological Data Likelihood Ratios and Personal Identificmentioning

confidence: 99%

Statistical basis for positive identification in forensic anthropology

Steadman

Adams

Konigsberg

2006

Am. J. Phys. Anthropol.

107

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“…It is reasonable to expect that underestimation (a false positive) could occur with a frequency defined by the significance level selected both for the CI of the mean weight and identity estimation. 4. Has the sampling method saved significant time and labor over the approach of weighing and chemically identifying every item needed to meet a threshold amount?…”

Section: Validation Of Sampling Methodsmentioning

confidence: 99%

“…Variations of the sampling approach and related issues in the context of seized-drug analysis have been described in journal articles and texts [1][2][3][4][5][6][7][8][9][10][11][12]. International standardizing bodies have published helpful terminologies and protocols on the subjects of sampling and statistics in general [13,14] and on seized-drug sampling in particular [14].…”

Section: Introductionmentioning

confidence: 99%

A probability-based sampling approach for the analysis of drug seizures composed of multiple containers of either cocaine, heroin, or Cannabis

Mario¹

2010

Forensic Science International

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“…During re-sampling, it is essential that the following principles are maintained: the properties of the sample are a true reflection of the properties of the population from which the samples were taken; and, each unit in the population has an equal chance of being selected [13] [14] [19]. For simplicity, after having observed that the external characteristics are the same, all the units can be put in a "black box" like a plastic bag, and a sample can be chosen randomly.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Evidence Analysis Cost Using Arbitrary Re-Sampling Techniques for Sample Influx into Forensic Science Laboratory

Manyele¹

2017

ENG

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This study analyzes the sample influx (samples per case file) into forensic science laboratory (FSL) and the corresponding analysis costs and uses arbitrary re-sampling plans to establish the minimum cost function. The demand for forensic analysis increased for all disciplines, especially biology/DNA between 2014 and 2015. While the average distribution of case files was about 42.5%, 40.6% and 17% for the three disciplines, the distribution of samples was rather different being 12%, 82.5% and 5.5% for samples requiring forensic biology, chemistry and toxicology analysis, respectively. Results show that most of the analysis workload was on forensic chemistry analysis. The cost of analysis for case files and the corresponding sample influx varied in the ratio of 35:6:1 and 28:12:1 for forensic chemistry, biology/DNA and toxicology for year 2014 for 2015, respectively. In the two consecutive years, the cost for forensic chemistry analysis was comparatively very high, necessitating re-sampling. The time series of sample influx in all disciplines are strongly stochastic, with higher magnitude for chemistry, biology/DNA and toxicology, in this order. The PDFs of sample influx data are highly skewed to the right, especially forensic toxicology and biology/DNA with peaks at 1 and 3 samples per case file. The arbitrary re-sampling plans were best suited to forensic chemistry case files (where re-sampling conditions apply). The locus of arbitrary number of samples to take from the submitted forensic samples was used to establish the minimum and scientifically acceptable samples by applying minimization function developed in this paper. The cost minimization function was also developed based on the average cost per sample and choice of re-sampling plans depending on the range of sample influx, from which the savings were determined and maximized. Thus, the study gives a forensic scientist a business model and scientific decision making tool on minimum number of samples to analyze focusing on savings on analysis cost.

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How Many Samples from a Drug Seizure Need to Be Analyzed?

Cited by 14 publications

References 3 publications

Statistical basis for positive identification in forensic anthropology

Statistical basis for positive identification in forensic anthropology

A probability-based sampling approach for the analysis of drug seizures composed of multiple containers of either cocaine, heroin, or Cannabis

Optimization of Evidence Analysis Cost Using Arbitrary Re-Sampling Techniques for Sample Influx into Forensic Science Laboratory

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