Two‐Dimensional Informative Array Testing

• Published in: Biometrics 2012-09, Vol.68 (3), p.793-804
• Main Authors: McMahan, Christopher S., Tebbs, Joshua M., Bilder, Christopher R.
• Format: Article
• Language: English
• Subjects: Algorithms; Arrays; BIOMETRIC METHODOLOGY; Biometrics; Biometry; Chlamydia; Chlamydia Infections - diagnosis; Design efficiency; Diagnostic Errors - statistics & numerical data; Disease screening; drugs; Efficiency; Female; genetics; Gonorrhea; Gonorrhea - diagnosis; Group testing; Humans; Infections; Infectious diseases; Infertility - prevention & control; Infertility Prevention Project; Male; Mass Screening - statistics & numerical data; Matrix pooling; Medical genetics; Medical screening; Models, Statistical; Nebraska; Pooled testing; Probability; Screening tests; Specimens; Testing; Urine
• ISSN: 0006-341X; 1541-0420
• DOI: 10.1111/j.1541-0420.2011.01726.x

Array‐based group‐testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed‐form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two‐dimensional array testing in a heterogeneous population. We then propose two “informative” array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per‐individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.