Imputation approaches for estimating diagnostic accuracy for multiple tests from partially verified designs

Biometrics

Volumn 63, Issue 3, 2007, Pages 947-957

  Albert, Paul S ^a  

^a NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Diagnostic accuracy; Gold standard evaluation; Latent class models; Mean imputation; Multiple tests; Partial verification; Prevalence; Semilatent class models; Sensitivity; Specificity; Verification bias

Indexed keywords

CLASS MODELS; DIAGNOSTIC ACCURACY; GOLD STANDARD EVALUATION; GOLD STANDARDS; LATENT CLASS MODEL; MEAN IMPUTATION; MULTIPLE TEST; PARTIAL VERIFICATION; PREVALENCE; SEMILATENT CLASS MODEL; SENSITIVITY; SPECIFICITY; STANDARD EVALUATIONS; VERIFICATION BIAS;

BIOMETRICS;

ACCURACY ASSESSMENT; CANCER; DESIGN; ESTIMATION METHOD; RADIOGRAPHY;

ASSAY; DATA ANALYSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST; DIGITAL RADIOGRAPHY; FEASIBILITY STUDY; GOLD STANDARD; HUMAN; LATENT PERIOD; METHODOLOGY; PREVALENCE; PRODUCTIVITY; RATING SCALE; REVIEW; SIMULATION; STOMACH CANCER;

EID: 34548394671     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2006.00734.x     Document Type: Review

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