Simultaneously Modelling Clustered Marginal Counts and Multinomial Proportions with Zero Inflation with Application to Analysis of Osteoporotic Fractures Data
- Resource Type
- Authors
- Renjun Ma; Gary Sneddon; M. Tariqul Hasan
- Source
- Journal of the Royal Statistical Society Series C: Applied Statistics. 67:185-200
- Subject
- 0301 basic medicine
Statistics and Probability
Mixed model
National Health and Nutrition Examination Survey
Zero inflation
Disease cluster
01 natural sciences
010104 statistics & probability
03 medical and health sciences
030104 developmental biology
Overdispersion
Statistics
Econometrics
Fracture (geology)
Multinomial distribution
0101 mathematics
Statistics, Probability and Uncertainty
Joint (geology)
Mathematics
- Language
- ISSN
- 1467-9876
0035-9254
Summary Osteoporotic fractures are known to be highly recurring. We investigate bone-dependent and bone-independent risk factors of osteoporotic fracture frequency and relative proportions at various body locations by using the data from the osteoporotic fracture study that was conducted by the National Health and Nutrition Examination Survey, 2007–2008. We propose a new zero-inflated baseline category multinomial mixed model to characterize the clustered count responses and multinomial proportions by subject simultaneously while taking account of zero inflation and randomness of cluster sizes. Our approach gives additional insights into the risk factors of osteoporotic fracture frequencies at various body locations. This joint modelling of fracture frequency also allows us to characterize relative proportion patterns at various body locations by subject between men and women across age. These findings have clear policy relevance to appropriate osteoporotic fracture prevention and resource allocation.