Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard

Statistics in Medicine

Volumn 35, Issue 6, 2016, Pages 859-876

  Jafarzadeh, S Reza ^a   Johnson, Wesley O ^b   Gardner, Ian A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b 5226 Donald Bren Hall   (United States)

Author keywords

AUC; Bayes' theorem; Biomarker combination; Imperfect reference standard; Receiver operating characteristic curve

Indexed keywords

BIOLOGICAL MARKER;

ANTIBODY DETECTION; ARTICLE; BAYES THEOREM; BOVINE; DIAGNOSTIC ACCURACY; ENZYME LINKED IMMUNOSORBENT ASSAY; INFERENTIAL STATISTICS; MULTIVARIATE ANALYSIS; NONHUMAN; PARATUBERCULOSIS; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; REFERENCE VALUE; SENSITIVITY AND SPECIFICITY; SIMULATION; STATISTICAL MODEL; ANIMAL; AREA UNDER THE CURVE; COMPUTER SIMULATION; DIFFERENTIAL DIAGNOSIS;

ANIMALS; AREA UNDER CURVE; BAYES THEOREM; BIOMARKERS; CATTLE; COMPUTER SIMULATION; DIAGNOSIS, DIFFERENTIAL; LIKELIHOOD FUNCTIONS; MODELS, STATISTICAL; PARATUBERCULOSIS; ROC CURVE;

EID: 84956580247     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6745     Document Type: Article

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