Grant Number:	1R13CA091917-01 Interpret this number
Primary Investigator:	Kass, Robert
Organization:	Carnegie-Mellon University
Project Title:	Symposium on Case Studies in Bayesian Statistics-Vi
Fiscal Year:	2001

DESCRIPTION: (provided by applicant) A symposium entitiled "Bayesian Statistics in Science and Technology: Case Studies VI" will be held at Carnegie-Mellon University in Pittsburgh, Pennsylvania, on Friday September 28 and Saturday September 29, 2001. The symposium will include two extended presentations of applications of Bayesian methods in problems in which the statistician was an integral member of the research team, and one case study of statistical methods analyzed by a panel of three experts. Two contributed poster sessions will also be held. The objectives of the symposium are to: (i) Highlight the close interplay of statistical theory and applications in the context of substantive scientific research. (ii) Contribute to the development of Bayesian statistics, by identifying problems without standard solution, and encouraging the extension of the theory and its implemtation so that posible approaches to analyses may be found. (iii) Bring to the fore the topic of reporting of Bayesian statistical analyses to the scientific community, and discuss effective and relevant means of communicating both the methods used in, and the conclusions drawn from quantitative analyses. (iv) Provide a small meeting atmosphere for young researchers and graduate students to present their work and to interact with senior colleagues, and to learn about the recent advances in implementation of Bayesian methods in substantive problems. (v) Encourage the collaboration between statisticians and researchers in subject matter disciplines, by emphasizing the many challenging statistical problems that arise in the course of scientific research. (vi) Disseminate the results of the research presented at the workshop by publishing a volume containing well-documented and peer-reviewed case studies and data sets, and other selected workshop presentations. As increasingly much background information becomes available to scientists undertaking an investigation, it is important to utilize previous knowledge effectively in designing studies and analyzing data. Bayesian statistical methods are tailored to this purpose. There have been many recent advances in Bayesian statistical theory and computation, but scientific meetings rarely spendsubstantial time discussing applications. The purpose of this symposium is to concentrate attention solely on applications of Bayesian statistics. The goal is to elucidate the interplay between theory and practice and thereby identify sucessful methods and indicate important directions for future research.




Survivin expression in oral squamous cell carcinoma.
Authors: Lo Muzio L. , Pannone G. , Staibano S. , Mignogna M.D. , Rubini C. , Mariggiò M.A. , Procaccini M. , Ferrari F. , De Rosa G. , Altieri D.C. .
Source: British journal of cancer, 2003-12-15; 89(12), p. 2244-8.
PMID: 14676801
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Survivin, a potential early predictor of tumor progression in the oral mucosa.
Authors: Lo Muzio L. , Pannone G. , Leonardi R. , Staibano S. , Mignogna M.D. , De Rosa G. , Kudo Y. , Takata T. , Altieri D.C. .
Source: Journal of dental research, 2003 Nov; 82(11), p. 923-8.
PMID: 14578507
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