Politomic Erased Respondent Method (PERM) for the joint assessment of two dichotomous characteristics, with an application to the polydrug use of cocaine and cannabis by simulation.
The recently introduced ERM (Erased Respondent Method) allows the prevalence of a characteristic to be estimated in a certain population by using the results obtained from groups of subjects rather than the data from single subjects. In the case of qualitative analytical surveys, the method allows the said prevalence to be estimated on the basis of the results derived from the analyses of pools of single samples. In this way, the knowledge of the individual data is not longer needed for the purpose of the estimates. This is particularly useful when there is sensitive data. In this work, it is shown how the ERM can also be applied to polytomic-type responses (e.g. negative, positive to A, positive to B, positive to A and B) in relation to qualitative analytical surveys. It is therefore possible to also estimate the prevalence of positive subjects to more characteristics on the basis of this extension of the ERM, we named it PERM (Politomic ERM). An application of the method is given by simulation in this work: an hypothetical street check in which one can estimate the prevalence of drivers under the influence of cocaine and/or cannabis (estimate of the prevalence of the users of a single substance and the prevalence of polydrug users). An important application of the method seems up to now to be in the casual street monitoring of the driver of a vehicle under the influence of alcohol and/or drugs of abuse.
Taggi
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F
Environment and Trauma Division, Department of Environment and Primary Prevention, Istituto Superiore di Sanità, Rome, Italy. franco.taggi@iss.it
D000063:Accidents, Traffic; D000435:Alcoholic Intoxication / Q000453:epidemiology*; D001334:Automobile Driving; D016010:Binomial Distribution; D019970:Cocaine-Related Disorders / Q000175:diagnosis / Q000453:epidemiology*; D006801:Humans; D002189:Marijuana Abuse / Q000175:diagnosis / Q000453:epidemiology*; D015233:Models, Statistical; D008962:Models, Theoretical; D015995:Prevalence; D015813:Substance Abuse Detection