Comparing the performance of propensity score methods in healthcare database studies with rare outcomes

Statistics in Medicine

Volumn 36, Issue 12, 2017, Pages 1946-1963

  Franklin, Jessica M ^a   Eddings, Wesley ^a   Austin, Peter C ^b   Stuart, Elizabeth A ^c   Schneeweiss, Sebastian ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b INSTITUTE FOR CLINICAL EVALUATIVE SCIENCES   (Canada)

^c JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

epidemiology; healthcare databases; propensity score; risk ratio; simulation

Indexed keywords

COHORT ANALYSIS; DATA BASE; HUMAN; LOGISTIC REGRESSION ANALYSIS; PROPENSITY SCORE; RISK FACTOR; SIMULATION; BAYES THEOREM; CAUSALITY; COMPARATIVE STUDY; FACTUAL DATABASE; PROBABILITY; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL BIAS; STATISTICAL MODEL; TREATMENT OUTCOME;

BAYES THEOREM; BIAS; CAUSALITY; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; HUMANS; LIKELIHOOD FUNCTIONS; LOGISTIC MODELS; PROBABILITY; PROPENSITY SCORE; REGRESSION ANALYSIS; TREATMENT OUTCOME;

EID: 85013290379     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.7250     Document Type: Article

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