Screening without a “Gold Standard”: The Hui-Walter Paradigm Revisited

• Published in: American journal of epidemiology 2001-05, Vol.153 (9), p.921-924
• Main Authors: Johnson, Wesley O., Gastwirth, Joseph L., Pearson, Larry M.
• Format: Article
• Language: English
• Subjects: Bayes Theorem; Bayesian approach; Biological and medical sciences; diagnostic test; Epidemiology; General aspects; Gibbs sampler; Humans; likelihood; Likelihood Functions; Mass Screening - methods; Mass Screening - standards; Medical sciences; Methodology; Models, Statistical; Prevalence; Public health. Hygiene; Public health. Hygiene-occupational medicine; Reproducibility of Results; Sample Size; Sensitivity and Specificity; Strongyloidiasis - epidemiology
• ISSN: 0002-9262; 1476-6256; 0002-9262
• DOI: 10.1093/aje/153.9.921

The authors consider screening populations with two screening tests but where a definitive “gold standard” is not readily available. They discuss a recent article in which a Bayesian approach to this problem is developed based on data that are sampled from a single population. It was subsequently pointed out that such inferences will not necessarily be accurate in the sense that standard errors for parameters may not decrease as n increases. This problem will generally occur when the data are insufficient to estimate all of the parameters as is the case when screening a single population with two tests. If both tests are applied to units sampled from two populations, however, this particular difficulty disappears. In this article the authors further examine this issue and develop an approach based on sampling two populations that yields increasingly accurate inferences as the sample size increases.