THE CREDIBILITY OF DRUG TESTS - A MULTISTAGE BAYESIAN-ANALYSIS

The authors show that even when drug tests are extremely accurate by c onventional measures, under some circumstances they will yield a high ''false accusation rate'' (that is, a high percentage of those testing positive for drugs will not have drugs in their systems). For example , if a drug-testing process that produces only one false positive per 2,000 drug-free specimens, and no false negatives, is administered to a population in which 0.1 % of the people use the targeted drugs, one- third of those identified as drug users will be falsely accused. The a uthors propose a multi-stage Bayesian algorithm-an approach commonly u sed in management science but novel to industrial relations-that assur es that a drug-testing process will have a low enough false accusation rate to provide credible evidence of drug use. They also identify oth er types of employee evaluations to which Bayesian modeling could be a pplied.