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Hierarchical Bayes Analysis of Smoking and Lung Cancer Data
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 Title & Authors
Hierarchical Bayes Analysis of Smoking and Lung Cancer Data
Oh, Man-Suk; Park, Hyun-Jin;
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 Abstract
Hierarchical models are widely used for inference on correlated parameters as a compromise between underfitting and overfilling problems. In this paper, we take a Bayesian approach to analyzing hierarchical models and suggest a Markov chain Monte Carlo methods to get around computational difficulties in Bayesian analysis of the hierarchical models. We apply the method to a real data on smoking and lung cancer which are collected from cities in China.
 Keywords
Hierarchical model;Correlated parameters;Markov chain Monte Carlo;Meta analysis;
 Language
English
 Cited by
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 References
1.
범주형자료분석, 1998.

2.
몬테칼로 적분, 1995.

3.
Statistics in Medicine, 1992. vol.11. pp.141-158 crossref(new window)

4.
Small Area Statistics: An International Symposium, 1987.

5.
Journal of the American Statistical Association, 1979. vol.74. pp.269-277 crossref(new window)

6.
Journal of the American Statistical Association, 1990. vol.85. pp.398-409 crossref(new window)

7.
Bayesian Data Analysis, 1995. pp.119-156

8.
The estimation of probabilities: An essay on modern Bayesian methods, 1965.

9.
Journal of the American Statistical Association, 1965. vol.60. pp.806-825 crossref(new window)

10.
Foundations of Statistical Science, 1971.

11.
International Journal of Epidemiology, 1992. vol.21. pp.197-201 crossref(new window)

12.
Biometrics, 1987. vol.43. pp.301-311 crossref(new window)

13.
Statistics in Medicine, 1991. vol.10. pp.95-112 crossref(new window)

14.
Applied Bayesian and classicial inferences: The case of the federalist papers, 1964.

15.
Computational Statistics and Data Analysis, 1999. vol.29. pp.411-427 crossref(new window)

16.
American Journal of Epidemiology, 1993. vol.138. pp.430-442

17.
Simulation and the Monte Carlo Method, 1981.