Bayesian inference from incomplete longitudinal data: A simple method to quantify sensitivity to nonignorable dropout

Statistics in Medicine

Volumn 28, Issue 22, 2009, Pages 2725-2747

  Xie, Hui ^a  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Bayesian statistics; General linear model; Linear mixed model; MAR; Nonignorable; Sensitivity analysis

Indexed keywords

ARTICLE; BAYES THEOREM; CALCULATION; DATA ANALYSIS; HUMAN; LINEAR SYSTEM; LOGISTIC REGRESSION ANALYSIS; LONGITUDINAL STUDY; NONHUMAN; QUANTITATIVE STUDY; RHEUMATOID ARTHRITIS; SAMPLE SIZE; SENSITIVITY ANALYSIS; SIMULATION; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; VALIDITY;

ANIMALS; BAYES THEOREM; LINEAR MODELS; LONGITUDINAL STUDIES; MALE; PATIENT DROPOUTS; RANDOM ALLOCATION; RATS; RATS, WISTAR; SENSITIVITY AND SPECIFICITY; TESTOSTERONE;

EID: 70449435789     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3655     Document Type: Article

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