Modeling type 1 and type 2 diabetes mellitus incidence in youth: An application of Bayesian hierarchical regression for sparse small area data

Spatial and Spatio-temporal Epidemiology

Volumn 2, Issue 1, 2011, Pages 23-33

  Song Hae Ryoung, H R ^a   Lawson, Andrew ^b   D'Agostino, Ralph B ^c   Liese, Angela D ^a  

^a UNIVERSITY OF SOUTH CAROLINA   (United States)

^b MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

^c WAKE FOREST SCHOOL OF MEDICINE   (United States)

Author keywords

Bayesian; Diabetes; Sparse data; Sparse Poisson convolution model; Sparse Poisson MCAR model

Indexed keywords

ADOLESCENT; AGE DISTRIBUTION; ARTICLE; BAYES THEOREM; GEOGRAPHIC DISTRIBUTION; HUMAN; INCIDENCE; INSULIN DEPENDENT DIABETES MELLITUS; JUVENILE; NON INSULIN DEPENDENT DIABETES MELLITUS; POISSON DISTRIBUTION; PRIORITY JOURNAL; RACE DIFFERENCE; SEX RATIO; SIMULATION; STATISTICAL MODEL; UNITED STATES;

ADOLESCENT; BAYES THEOREM; BIOMETRY; CHILD; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; GEOGRAPHY, MEDICAL; HUMANS; INCIDENCE; MODELS, STATISTICAL; POISSON DISTRIBUTION; SOUTH CAROLINA; YOUNG ADULT;

EID: 78650518993     PISSN: 18775845     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sste.2010.09.008     Document Type: Article

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