Quantitative Erased Respondent Method (QERM): using quantitative group data as an alternative to quantitative individual data. A simulated application to road checks for drivers under the influence of cocaine.
The Erased Respondent Method (ERM) allows the prevalence of a characteristic to be estimated without needing to know the state of the individual statistical units. A recent extension of the method, which also did not make use of individual data, also estimated the prevalence of two or more characteristics in the same individual (PERM, Politomic ERM). In this paper, ERM is extended further to quantitative data coming from analytical determinations, considering pools of samples instead of individual samples. The extension of the method above described, we named it with the acronym QERM (Quantitative ERM), allows to estimate (only on the ground of analytical determinations made from pools of individual samples) the average and the standard deviation of the distribution of the determinations concerning only positive individual samples. By referring to road controls for driving under the influence of abuse drugs that constitute pools of biological material from more drivers, with the ERM we are able to estimate the prevalence of subjects that are positive for a certain substance, while with the QERM we can estimate the mean and standard deviation of the quantity of the substance measured in biological liquids only from the subjects that are positive to the substance. In order to better clarify this new method, an application to a road check for driving under the influence of cocaine will also be presented that was obtained by simulation. The application fields in Public Health for ERM, PERM and QERM are many; however in our opinion the most interesting areas of application are road traffic, occupational and sport safety.
Taggi
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F
Dept of Environment and Primary Prevention, Section "Environment and Trauma", ISS - Istituto Superiore di Sanità, National Institute of Health, Rome, Italy. franco.taggi@iss.it
D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D000465:Algorithms; D001334:Automobile Driving; D016010:Binomial Distribution; D019970:Cocaine-Related Disorders / Q000175:diagnosis* / Q000453:epidemiology*; D003198:Computer Simulation; D006801:Humans; D008432:Mathematical Computing; D015233:Models, Statistical; D015995:Prevalence; D011634:Public Health; D012384:Rome / Q000453:epidemiology; D012494:Sampling Studies; D015813:Substance Abuse Detection / Q000379:methods