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E-raamat: Case Studies in Bayesian Statistics: Volume IV

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  • Sari: Lecture Notes in Statistics 140
  • Ilmumisaeg: 06-Dec-2012
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781461215028
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  • Formaat: PDF+DRM
  • Sari: Lecture Notes in Statistics 140
  • Ilmumisaeg: 06-Dec-2012
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781461215028
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The 4th Workshop on Case Studies in Bayesian Statistics was held at the Car­ negie Mellon University campus on September 27-28, 1997. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the four invited case studies with the accompanying discus­ sion as well as nine contributed papers selected by a refereeing process. While most of the case studies in the volume come from biomedical research the reader will also find studies in environmental science and marketing research. INVITED PAPERS In Modeling Customer Survey Data, Linda A. Clark, William S. Cleveland, Lorraine Denby, and Chuanhai LiD use hierarchical modeling with time series components in for customer value analysis (CVA) data from Lucent Technologies. The data were derived from surveys of customers of the company and its competi­ tors, designed to assess relative performance on a spectrum of issues including product and service quality and pricing. The model provides a full description of the CVA data, with random location and scale effects for survey respondents and longitudinal company effects for each attribute. In addition to assessing the performance of specific companies, the model allows the empirical exploration of the conceptual basis of consumer value analysis. The authors place special em­ phasis on graphical displays for this complex, multivariate set of data and include a wealth of such plots in the paper.

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Invited Papers Modeling Customer Survey Data 3(56) Clark, L.A. Cleveland, W.S. Denby, L. Liu, C. Discussion: N.G. Best 42(6) Discussion: E.T. Bradlow and K. Kalyanam 48(3) Discussion: P.E. Rossi 51(1) Rejoinder 52(7) Functional Connectivity in the Cortical Circuits Subserving Eye Movements 59(74) Genovese, C.R. Sweeney, J.A. Discussion: J. Raz and C. Liu 121(5) Discussion: Y.N. Wu 126(3) Rejoinder 129(4) Modeling Risk of Breast Cancer and Decisions about Genetic Testing 133(72) Parmigiani, G. Berry, D.A. Iversen, E.S., Jr. Muller, P. Schildkraut, J.M. Winer, E.P. Discussion: S. Greenhouse 189(1) Discussion: L. Kessler 189(3) Discussion: N.D. Singpurwalla 192(2) Discussion: S.J. Skates 194(5) Rejoinder 199(6) The Bayesian Approach to Population Pharmacokinetic/pharmacodynamic Modeling 205(64) Wakefield, J. Aarons, L. Racine-Poon, A. Discussion: F. Bois 253(4) Discussion: M. Davidian 257(5) Discussion: S. Greenhouse 262(1) Rejoinder: 262(7) Contributed Papers Longitudinal Modeling of the Side Effects of Radiation Therapy 269(18) Adak, S. Sarkar, A. Analysis of Hospital Quality Monitors using Hierarchical Time Series Models 287(16) Aguilar, O. West, M. Spatio-Temporal Hierarchical Models for Analyzing Atlanta Pediatric Asthma ER Visit Rates 303(18) Carlin, B.P. Xia, H. Devine, O. Tolbert, P. Mulholland, J. Validating Bayesian Prediction Models: a Case Study in Genetic Susceptibility to Breast Cancer 321(18) Iversen, E.S. Jr. Parmigiani, G. Berry, D.A. Mixture Models in the Exploration of Structure-Activity Relationships in Drug Design 339(16) Paddock, S. West, M. Young, S.S. Clyde, M. Population Models for Hematologic Data 355(12) Palmer, J.L. Muller, P. A Hierarchical Spatial Model for Constructing Wind Fields from Scatterometer Data in the Labrador Sea 367(16) Royle, J.A. Berliner, L.M. Wikle, C.K. Milliff, R. Redesigning a Network of Rainfall Stations 383(12) Sanso, B. Muller, P. Using PSA to Detect Prostate Cancer Onset: An Application of Bayesian Retrospective and Prospective Changepoint Identification 395(18) Slate, E.H. Clark, L.C. Author Index 413(12) Subject Index 425