Identifying influential observations in Bayesian models by using Markov chain Monte Carlo

Statistics in Medicine

Volumn 31, Issue 11-12, 2012, Pages 1238-1248

  Jackson, Dan ^a   White, Ian R ^a   Carpenter, James ^b  

^a MRC BIOSTATISTICS UNIT   (United Kingdom)

^b LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

Bayesian methods; Generalised linear models; Influence; Markov chain Monte Carlo

Indexed keywords

ARTICLE; BAYES THEOREM; CHILD DEATH; MATHEMATICAL COMPUTING; MAXIMUM LIKELIHOOD METHOD; MONTE CARLO METHOD; PROBABILITY; REGRESSION ANALYSIS; RISK FACTOR; SIMULATION; STATISTICAL MODEL; SUDDEN DEATH;

BAYES THEOREM; CASE-CONTROL STUDIES; COMPUTER SIMULATION; HUMANS; INFANT; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; REGRESSION ANALYSIS; SUDDEN INFANT DEATH;

EID: 84861197524     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4356     Document Type: Article

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