High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions

Statistics in Medicine

Volumn 34, Issue 5, 2014, Pages 753-781

  Neugebauer, Romain ^a   Schmittdiel, Julie A ^a   Zhu, Zheng ^a   Rassen, Jeremy A ^b   Seeger, John D ^b   Schneeweiss, Sebastian ^b  

^a DIVISION OF RESEARCH   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Comparative effectiveness; Diabetes; High dimensional propensity score; Inverse probability weighting; Marginal structural model; Super learning

Indexed keywords

HEMOGLOBIN A1C;

ALGORITHM; ARTICLE; CALCULATION; COHORT ANALYSIS; COMPARATIVE EFFECTIVENESS; COVARIANCE; ELECTRONIC MEDICAL RECORD; HIGH DIMENSIONAL PROPENSITY SCORE ALGORITHM; HUMAN; INVERSE PROBABILITY WEIGHTING ESTIMATION; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; NON INSULIN DEPENDENT DIABETES MELLITUS; OBSERVATIONAL STUDY; PROPENSITY SCORE; RETROSPECTIVE STUDY; SELECTION BIAS; SIMULATION; STATISTICAL MODEL; STATISTICAL PARAMETERS; SUPER LEARNING; ADULT; BIOSTATISTICS; BLOOD; COMPUTER SIMULATION; DIABETES MELLITUS, TYPE 2; ELECTRONIC HEALTH RECORD; EPIDEMIOLOGY; FACTUAL DATABASE; FEMALE; MALE; MULTICENTER STUDY (TOPIC); PROBABILITY; STATISTICS AND NUMERICAL DATA;

ADULT; ALGORITHMS; BIOSTATISTICS; COHORT STUDIES; COMPARATIVE EFFECTIVENESS RESEARCH; COMPUTER SIMULATION; CONFOUNDING FACTORS (EPIDEMIOLOGY); DATABASES, FACTUAL; DIABETES MELLITUS, TYPE 2; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; MALE; MODELS, STATISTICAL; MULTICENTER STUDIES AS TOPIC; OBSERVATIONAL STUDIES AS TOPIC; PROBABILITY; PROPENSITY SCORE; RETROSPECTIVE STUDIES; SELECTION BIAS;

EID: 84921600598     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6377     Document Type: Article

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