The Credibility of Drug Tests
A Multi-Stage Bayesian Analysis
Bibliographic Data
| ID | 3489411 |
|---|---|
| Authors | Darold T Barnum, John M Gleason |
| Year | 1994 |
| Volume | 47 |
| Issue | 4 |
| Pages | 610-621 |
| Publication date | 1994-07-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Industrial and Labor Relations Review (JOURNAL) |
| Journal identifiers | ISSN: 0019-7939 • E-ISSN: 2162-271X |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/001979399404700406 |
| OpenAlex | W1988069894, W4229933076 |
| Language | EN |
| Citations received | 1 |
| References cited | 10 |
The authors show that even when drug tests are extremely accurate by conventional 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 authors propose a multi-stage Bayesian algorithm-an approach commonly used in management science but novel to industrial relations-that assures that a drug-testing process will have a low enough false accusation rate to provide credible evidence of drug use. They also identify other types of employee evaluations to which Bayesian modeling could be applied
Bayesian probability · Biology · Credibility · Data mining · Drug · Econometrics · Economics · False accusation · False positive rate · Multiple comparisons problem · Political science · Population · Risk analysis (engineering) · Stage (stratigraphy) · Statistics · Advanced Statistical Process Monitoring · Artificial Intelligence · Computer Science · Law · Mathematics · Medicine · Pharmacology · Psychology · Social Psychology · Statistical Methods in Clinical Trials
| Citations per year | 0.1 |
|---|---|
| Citation span | 2006 - 2006 (1) |
| Highly cited | No |