A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting AMI mortality

Statistics in Medicine

Volumn 26, Issue 15, 2007, Pages 2937-2957

  Austin, Peter C ^a,b  

^a INSTITUTE FOR CLINICAL EVALUATIVE SCIENCES   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

Acute myocardial infarction; Classification trees; Generalized additive models; Logistic regression; Multivariate adaptive regression splines; Predictive model; Recursive partitioning; Regression trees; Validation

Indexed keywords

ACCURACY; ACUTE HEART INFARCTION; ADULT; AGED; ARTICLE; CANADA; CONTROLLED STUDY; CORONARY ARTERY BYPASS GRAFT; FEMALE; HOSPITAL ADMISSION; HOSPITALIZATION; HUMAN; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MALE; MORTALITY; MULTIVARIATE ANALYSIS; PERCUTANEOUS CORONARY INTERVENTION; PERFORMANCE; PREDICTION; REGRESSION ANALYSIS; ROC CURVE; STATISTICAL MODEL; VALIDATION STUDY;

DATA INTERPRETATION, STATISTICAL; FEMALE; FORECASTING; HUMANS; LOGISTIC MODELS; MALE; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; MYOCARDIAL INFARCTION; ONTARIO; ROC CURVE;

EID: 34250613098     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.2770     Document Type: Article

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