Corrected ROC analysis for misclassified binary outcomes

Statistics in Medicine

Volumn 36, Issue 13, 2017, Pages 2148-2160

  Zawistowski, Matthew ^a,b   Sussman, Jeremy B ^a,c   Hofer, Timothy P ^a,c   Bentley, Douglas ^a   Hayward, Rodney A ^a,c   Wiitala, Wyndy L ^a  

^a VETERANS AFFAIRS MEDICAL CENTER   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

electronic health records; misclassification; precision medicine; risk prediction modeling; ROC analysis

Indexed keywords

ACCURACY; ALGORITHM; AREA UNDER THE CURVE; ARTICLE; BAYES THEOREM; BIOLOGY; BOOTSTRAPPING; CLASSIFICATION; COHORT ANALYSIS; ELECTRONIC HEALTH RECORD; HEALTH CARE PLANNING; HEALTH CARE UTILIZATION; HOSPITALIZATION; LOGISTIC REGRESSION ANALYSIS; MOLECULAR BIOLOGY; OUTCOME ASSESSMENT; PERSONALIZED MEDICINE; PREDICTION; PREDICTIVE VALUE; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; RISK ASSESSMENT; SIMULATION; TRAINING; VALIDATION PROCESS; GOVERNMENT; HUMAN; PROCEDURES; STATISTICAL BIAS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; UNITED STATES;

AREA UNDER CURVE; BIAS; ELECTRONIC HEALTH RECORDS; HOSPITALIZATION; HUMANS; MODELS, STATISTICAL; RISK ASSESSMENT; ROC CURVE; UNITED STATES; UNITED STATES DEPARTMENT OF VETERANS AFFAIRS;

EID: 85014139698     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.7260     Document Type: Article

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