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Bayesian generalized linear mixed modeling of Tuberculosis using informative priors
- Source :
- PLoS ONE, Vol 12, Iss 3, p e0172580 (2017), PLoS ONE
- Publication Year :
- 2017
- Publisher :
- Public Library of Science (PLoS), 2017.
-
Abstract
- TB is rated as one of the world's deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014.
- Subjects :
- RNA viruses
Bacterial Diseases
Computer science
Normal Distribution
Social Sciences
lcsh:Medicine
02 engineering and technology
Pathology and Laboratory Medicine
01 natural sciences
Geographical locations
South Africa
010104 statistics & probability
Bayes' theorem
Mathematical and Statistical Techniques
Immunodeficiency Viruses
Sociology
Medicine and Health Sciences
0202 electrical engineering, electronic engineering, information engineering
Econometrics
lcsh:Science
Multidisciplinary
Regression analysis
Actinobacteria
Bayesian statistics
Infectious Diseases
Medical Microbiology
Viral Pathogens
Viruses
Physical Sciences
020201 artificial intelligence & image processing
Pathogens
Bayesian Statistics
Statistics (Mathematics)
Research Article
Markov Models
Bayesian probability
Research and Analysis Methods
Bayesian inference
Microbiology
Education
Set (abstract data type)
Normal distribution
Retroviruses
Prior probability
Tuberculosis
Humans
Statistical Methods
0101 mathematics
Microbial Pathogens
Educational Attainment
Bacteria
Lentivirus
lcsh:R
Organisms
Biology and Life Sciences
HIV
Bayes Theorem
Models, Theoretical
Tropical Diseases
Probability Theory
Probability Distribution
Africa
lcsh:Q
People and places
Mathematics
Mycobacterium Tuberculosis
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 12
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....fa4802864ab4d348633279bd68facc8f