On Estimating Diagnostic Accuracy From Studies With Multiple Raters and Partial Gold Standard Evaluation

• Published in: Journal of the American Statistical Association Vol. 103; no. 481; pp. 61 - 73
• Main Authors: Albert, Paul S, Dodd, Lori E
• Format: Journal Article
• Language: English
• Published: Alexandria, VA Taylor & Francis 01.03.2008; American Statistical Association; Taylor & Francis Ltd
• Subjects: Accuracy; Applications; Applications and Case Studies; Calculus of variations and optimal control; Cancer; Diagnosis; Diagnostic error; Diagnostic errors; Digital technology; Diseases; Estimate reliability; Estimation bias; Exact sciences and technology; Gastrointestinal diseases; General topics; Gold standard; Illness; Latent class models; Mathematical analysis; Mathematics; Medical diagnosis; Medical errors; Medical imaging; Misclassification; Modeling; Parametric inference; Parametric models; Probability and statistics; Public health; Radiology; Sampling bias; Sciences and techniques of general use; Semilatent class models; Simulations; Standardized tests; Statistical analysis; Statistical data; Statistical methods; Statistical models; Statistics; Estimation error; Error estimation; Latent class models; Estimator robustness; Probability; Non parametric estimation; Statistical estimation; Probability distribution; Adaptive estimation; Diagnostic error; Statistical method; Diagnostic test; Simulation; Experimental design; Misclassification; Application; Latent class model; Biased estimation; Semilatent class models

We are often interested in estimating sensitivity and specificity of a group of raters or a set of new diagnostic tests in situations in which gold standard evaluation is expensive or invasive. Numerous authors have proposed latent modeling approaches for estimating diagnostic error without a gold s...