Evaluating uses of data mining techniques in propensity score estimation: A simulation study

Pharmacoepidemiology and Drug Safety

Volumn 17, Issue 6, 2008, Pages 546-555

  Setoguchi, Soko ^a   Schneeweiss, Sebastian ^a   Brookhart, M Alan ^a   Glynn, Robert J ^a   Cook, E Francis ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Logistic regression; Neural networks; Propensity score; Recursive partitioning

Indexed keywords

ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; COHORT ANALYSIS; CORRELATION ANALYSIS; COVARIANCE; DATA MINING; EXPOSURE PROPENSITY SCORE; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; NONLINEAR SYSTEM; PRIORITY JOURNAL; RECURSIVE PARTITIONING; SIMULATION; STATISTICAL MODEL; SYSTEMATIC ERROR; COMPUTER SIMULATION; EPIDEMIOLOGY; HUMAN; METHODOLOGY; MONTE CARLO METHOD; PHARMACOEPIDEMIOLOGY; STATISTICAL ANALYSIS;

BIAS (EPIDEMIOLOGY); COHORT STUDIES; COMPUTER SIMULATION; CONFOUNDING FACTORS (EPIDEMIOLOGY); DATA INTERPRETATION, STATISTICAL; HUMANS; LOGISTIC MODELS; MONTE CARLO METHOD; NEURAL NETWORKS (COMPUTER); PHARMACOEPIDEMIOLOGY;

EID: 46349084991     PISSN: 10538569     EISSN: 10991557     Source Type: Journal    
DOI: 10.1002/pds.1555     Document Type: Article

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