A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification

Statistics in Medicine

Volumn 26, Issue 29, 2007, Pages 5320-5334

  Jiang, Wenyu ^a,b   Simon, Richard ^a  

^a NATIONAL CANCER INSTITUTE   (United States)

^b Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

Bootstrap; Class prediction; Feature selection; Learning curve; Microarray data; Prediction error

Indexed keywords

ANALYTICAL ERROR; B CELL LYMPHOMA; BOOTSTRAPPING; CALCULATION; CONTROLLED STUDY; DNA MICROARRAY; GENE EXPRESSION; HUMAN; INTERMETHOD COMPARISON; LARGE CELL LYMPHOMA; METHODOLOGY; PREDICTION; REVIEW; SIMULATION;

ARTIFICIAL INTELLIGENCE; BIAS (EPIDEMIOLOGY); CLUSTER ANALYSIS; COMPUTER SIMULATION; CONFIDENCE INTERVALS; DATA INTERPRETATION, STATISTICAL; DIAGNOSIS, COMPUTER-ASSISTED; DISCRIMINANT ANALYSIS; GENE EXPRESSION PROFILING; GENETIC PREDISPOSITION TO DISEASE; GENETIC SCREENING; HUMANS; LOGISTIC MODELS; LYMPHOMA; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SAMPLING STUDIES; SENSITIVITY AND SPECIFICITY; STATISTICS, NONPARAMETRIC; TUMOR MARKERS, BIOLOGICAL;

EID: 37349009294     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.2968     Document Type: Review

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