Markov Chains for Random Urinalysis III: Daily Model and Drug Kinetics

Abstract

This is the third in a series of reports on the use of Markov chains for the analysis of random urinalysis programs. A Markov model for random drug urinalysis testing that allows for daily variations in testing probabilities was developed. The formulation allows for any fixed length cycle (e.g., week, month) . Drug kinetics and drug user gaming are incorporated into the Markov model via conditional probabilities. The Markov chain provides estimates of the distribution of time to detection and mean time to detection. The analyses have shown that time to detection varies dramatically with varying (observed) daily testing rates. Unequal daily testing rates provide opportunities for gaming drug users to extend the mean time to detection. Gaming is not possible with equal probabilities of testing across days. Drug urinalysis, Markov chains, Cocaine, Pharmacokinetics.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA275540

Entities

People

  • James P. Boyle
  • Theodore J. Thompson

Organizations

  • Bureau of Naval Personnel

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Detection
  • Differential Equations
  • Drug Abuse
  • Drug Users
  • Equations
  • Kinetics
  • Markov Chains
  • Markov Models
  • Military Personnel
  • Naval Personnel
  • Probability
  • Random Variables
  • Statistical Samples
  • Statistical Sampling
  • Stochastic Processes
  • Urinalysis

Fields of Study

  • Mathematics

Readers

  • Child and Adolescent Substance Abuse Science in Autism Spectrum Disorders.
  • Statistical inference.
  • Toxicology/Environmental Toxicology