Hierarchical Bayesian spatial modelling of small-area rates of non-rare disease

Statistics in Medicine

Volumn 22, Issue 10, 2003, Pages 1761-1773

  MacNab, Ying C ^a,b  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b Ctr Hlth Care Innov/Improvement   (Canada)

Author keywords

Bayesian hierarchical spatial model; Extra binomial variability; Health services research; Hybrid Markov chain; Mapping relative odd ratios; Monte Carlo

Indexed keywords

ARTICLE; BAYES THEOREM; CANADA; CHRONIC LUNG DISEASE; CONTROLLED STUDY; COVARIANCE; DISEASE SEVERITY; FEMALE; GEOGRAPHIC DISTRIBUTION; HEALTH SERVICE; HOSPITAL ADMISSION; HUMAN; INFANT; LOW BIRTH WEIGHT; MAJOR CLINICAL STUDY; MALE; MONTE CARLO METHOD; NEWBORN; NEWBORN INTENSIVE CARE; OUTCOMES RESEARCH; PREVALENCE; PROBABILITY; RANDOMIZATION; RESOURCE MANAGEMENT; RISK FACTOR; STATISTICAL ANALYSIS; STATISTICAL MODEL; VERY LOW BIRTH WEIGHT;

BAYES THEOREM; CANADA; CHRONIC DISEASE; HUMANS; INFANT, NEWBORN; INTENSIVE CARE UNITS, NEONATAL; LUNG DISEASES; MARKOV CHAINS; MONTE CARLO METHOD; RISK FACTORS; SMALL-AREA ANALYSIS;

EID: 0037847405     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.1463     Document Type: Article

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