Using an instrumental variable to test for unmeasured confounding

Statistics in Medicine

Volumn 33, Issue 20, 2014, Pages 3528-3546

  Guo, Zijian ^a   Cheng, Jing ^b   Lorch, Scott A ^c   Small, Dylan S ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Comparative effectiveness; Confounding; Instrumental variables; Observational study

Indexed keywords

ANALYTICAL ERROR; ARTICLE; ARTIFICIAL VENTILATION; CALCULATION; CONFOUNDING VARIABLE; CONTROLLED STUDY; DELIVERY; HUMAN; MATHEMATICAL COMPUTING; NEWBORN INTENSIVE CARE; OBSERVATIONAL STUDY; PREMATURITY; SIMULATION; ALGORITHM; COMPUTER SIMULATION; EPIDEMIOLOGY; FEMALE; MECHANICAL VENTILATOR; NEWBORN; PREGNANCY; PROCEDURES; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; TIME; UNITED STATES;

ALGORITHMS; COMPUTER SIMULATION; CONFOUNDING FACTORS (EPIDEMIOLOGY); DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; INFANT, NEWBORN; INTENSIVE CARE UNITS, NEONATAL; LIKELIHOOD FUNCTIONS; OBSERVATIONAL STUDIES AS TOPIC; PENNSYLVANIA; PREGNANCY; SENSITIVITY AND SPECIFICITY; TIME FACTORS; VENTILATORS, MECHANICAL;

EID: 84905513492     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6227     Document Type: Article

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