Reviewers
|
Book & Monographs
|
Conference
|
Contact Us
SEARCH
|
My Profile
|
My Shopping Cart
|
Logout
Home
Publication Ethics
Open Access Policy
Guidelines
Journals
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
Submit a Manuscript
Author Login
Author Registration
Forget Password
Journal Menu
Journal Home
Editorial Board
Guidelines for Authors
Indexing
Contents
Contents
Subscribe
Publication Ethics and Publication Malpractice Statement
Content
Volume 24 (2024)
Volume 24, Issue 3 (In progress)
Pg 399 - 526 (November 2024)
Volume 24, Issue 2
Pg 197 - 397 (July 2024)
Volume 24, Issue 1
Pg 1 - 196 (March 2024)
Volume 23 (2023)
Volume 23, Issue 3
Pg 227 - 327 (November 2023)
Volume 23, Issue 2
Pg 95 - 225 (July 2023)
Volume 23, Issue 1
Pg 1 - 94 (March 2023)
Volume 22 (2022)
Volume 22,
Pg 1 - 84 (December 2022)
Volume 21 (2022)
Volume 21,
Pg 1 - 154 (September 2022)
Volume 20 (2022)
Volume 20,
Pg 1 - 123 (June 2022)
Volume 19 (2022)
Volume 19,
Pg 1 - 144 (March 2022)
Volume 18 (2021)
Volume 18, Issue 3
Pg 305 - 504 (December 2021)
Volume 18, Issue 2
Pg 149 - 303 (August 2021)
Volume 18, Issue 1
Pg 1 - 147 (April 2021)
Volume 17 (2020)
Volume 17, Issue 2
Pg 307 - 602 (December 2020)
Volume 17, Issue 1
Pg 1 - 305 (June 2020)
Volume 16 (2019)
Volume 16, Issue 2
Pg 1 - 158 (December 2019)
Volume 16, Issue 1
Pg 1 - 111 (June 2019)
Volume 15 (2018)
Volume 15, Issue 2
Pg 83 - 173 (December 2018)
Volume 15, Issue 1
Pg 1 - 82 (June 2018)
Volume 14 (2017)
Volume 14, Issue 2
Pg 85 - 120 (December 2017)
Volume 14, Issue 1
Pg 1 - 84 (June 2017)
Volume 13 (2016)
Volume 13, Issue 2
Pg 103 - 238 (December 2016)
Volume 13, Issue 1
Pg 1 - 101 (June 2016)
Volume 12 (2015)
Volume 12, Issue 2
Pg 81 - 178 (December 2015)
Volume 12, Issue 1
Pg 1 - 80 (June 2015)
Volume 11 (2014)
Volume 11, Issue 2
Pg 89 - 168 (November 2014)
Volume 11, Issue 1
Pg 1 - 88 (June 2014)
Volume 10 (2013)
Volume 10, Issue 2
Pg 49 - 92 (November 2013)
Volume 10, Issue 1
Pg 1 - 48 (August 2013)
Volume 9 (2013)
Volume 9, Issue 2
Pg 67 - 118 (May 2013)
Volume 9, Issue 1
Pg 1 - 66 (February 2013)
Volume 8 (2012)
Volume 8, Issue 1-2 (Aug-Nov)
Pg 1 - 77 (November 2012)
Volume 7 (2012)
Volume 7, Issue 2
Pg 61 - 119 (May 2012)
Volume 7, Issue 1
Pg 1 - 59 (February 2012)
Volume 6 (2011)
Volume 6, Issue 2
Pg 77 - 120 (November 2011)
Volume 6, Issue 1
Pg 1 - 75 (August 2011)
Volume 5 (2011)
Volume 5, Issue 2
Pg 73 - 137 (May 2011)
Volume 5, Issue 1
Pg 1 - 71 (February 2011)
Volume 4 (2010)
Volume 4, Issue 3
Pg 213 - 311 (October 2010)
Volume 4, Issue 2
Pg 107 - 212 (June 2010)
Volume 4, Issue 1
Pg 1 - 105 (February 2010)
Volume 3 (2009)
Volume 3, Issue 3
Pg 171 - 256 (October 2009)
Volume 3, Issue 2
Pg 77 - 169 (June 2009)
Volume 3, Issue 1
Pg 1 - 75 (February 2009)
Volume 2 (2008)
Volume 2, Issue 3
Pg 169 - 261 (October 2008)
Volume 2, Issue 2
Pg 81 - 168 (June 2008)
Volume 2, Issue 1
Pg 1 - 80 (February 2008)
Volume 1 (2007)
Volume 1, Issue 3
Pg 217 - 306 (October 2007)
Volume 1, Issue 2
Pg 109 - 215 (June 2007)
Volume 1, Issue 1
Pg 1 - 108 (February 2007)
Categories
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
JP Journal of Biostatistics
JP Journal of Biostatistics
Volume 4, Issue 3, Pages 227 - 243 (October 2010)
SIMPLE EXACT BAYESIAN METHODS FOR INCORPORATING DIRECTIONAL PRIOR INFORMATION BASED ON A GENERALIZED
c
-DISTRIBUTION
Hisashi Noma
Abstract:
In many clinical and epidemiological studies, the prior knowledge or belief regarding treatment effect is clearly directional, i.e., pointing to protective effects or to harmful effects. Although recent developments in Bayesian computations such as the Markov Chain Monte Carlo methods have enabled to implement flexible modeling and inference, they involve complicated techniques and require additional special softwares. In this article, we develop exact Bayesian methods that can be conducted by simple concepts and computations. We consider a simple normal-approximated likelihood model and some class of skewed prior distributions. We introduce a generalized
c
-distribution, which constructs a conjugate family for the normal likelihood model, and show that it can be interpreted as a generalized model of the commonly-used normal prior model. We also show that the generalized
c
-distribution is derived as a posterior distribution by a gamma-prior model. In addition, we present simple exact computational methods for Bayesian inference based on the generalized
c
and gamma prior models. An application to an epidemiological study on the association of residential wire codes and magnetic fields with childhood leukemia is provided.
Keywords and phrases:
Bayesian methods, conjugate models, asymptotic normal approximation, a generalized
c
-distribution, gamma distribution.
Number of Downloads:
284 |
Number of Views:
698
Previous
Next
P-ISSN: 0973-5143
Journal Stats
Publication count:
321
Citation count (Google Scholar):
421
h10-index (Google Scholar):
10
h-index (Google Scholar):
10
Downloads :
83333
Views:
256138
Downloads/publish articles:
259.6
Citations (Google Scholar)/publish articles:
1.31
This website is best viewed at 1024x768 or higher resolution with Microsoft Internet Explorer 6 or newer.
