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Withdrawal time estimation of veterinary drugs: extending the range of statistical methods
Author(s) -
Fisch R. D.
Publication year - 2000
Publication title -
journal of veterinary pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.527
H-Index - 60
eISSN - 1365-2885
pISSN - 0140-7783
DOI - 10.1046/j.1365-2885.2000.00256.x
Subject(s) - withdrawal time , markov chain monte carlo , statistical inference , inference , bayesian probability , nonparametric statistics , reversible jump markov chain monte carlo , markov chain , range (aeronautics) , computer science , bayesian inference , statistics , econometrics , mathematics , medicine , artificial intelligence , engineering , colorectal cancer , colonoscopy , cancer , aerospace engineering
In order to use a drug in a food producing animal, evidence has to be provided that after a certain withdrawal time, drug residues in tissues, such as muscle meat, fat, liver, kidney etc., are below a given maximum residue limit (MRL), for a majority of animals. Several statistical methods, both regression based and nonparametric based methods, have been proposed, each relying on different sets of assumptions, which may or may not hold for the specific data situation. The purpose of this paper is to enrich the range of methods, i.e. to provide approaches for situations where current methods are inappropriate. Bayesian methods, using Markov chain Monte Carlo, are proposed to derive inference on the parameters of interest.