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Case Studies in Bayesian Statistics

Volume IV

  • Constantine Gatsonis
  • Robert E. Kass
  • Bradley Carlin
  • Alicia Carriquiry
  • Andrew Gelman
  • Isabella Verdinelli
  • Mike West

Part of the Lecture Notes in Statistics book series (LNS, volume 140)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Invited Papers

    1. Front Matter
      Pages 1-1
    2. Linda A. Clark, William S. Cleveland, Lorraine Denby, Chuanhai Liu
      Pages 3-57
    3. Christopher R. Genovese, John A. Sweeney
      Pages 59-132
    4. Giovanni Parmigiani, Donald A. Berry, Edwin Iversen Jr., Peter Müller, Joellen Schildkraut, Eric P. Winer
      Pages 133-203
    5. Jon Wakefield, Leon Aarons, Amy Racine-Poon
      Pages 205-265
  3. Contributed Papers

    1. Front Matter
      Pages 267-267
    2. Sudeshna Adak, Abhinanda Sarkar
      Pages 269-285
    3. Bradley P. Carlin, Hong Xia, Owen Devine, Paige Tolbert, James Mulholland
      Pages 303-320
    4. Edwin Iversen Jr., Giovanni Parmigiani, Donald Berry
      Pages 321-338
    5. Susan Paddock, Mike West, S. Stanley Young, Merlise Clyde
      Pages 339-353
    6. J. Lynn Palmer, Peter Müller
      Pages 355-366
    7. J. A. Royle, L. M. Berliner, C. K. Wikle, R. Milliff
      Pages 367-382
    8. Bruno Sansó, Peter Müller
      Pages 383-393
  4. Erratum

    1. Constantine Gatsonis, Bradley Carlin, Andrew Gelman, Mike West, Robert E. Kass, Alicia Carriquiry et al.
      Pages 431-431
  5. Back Matter
    Pages 413-429

About these proceedings

Introduction

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.

Keywords

Linda Volume bayesian statistics development form function functional marketing modeling statistics testing time series university

Editors and affiliations

  • Constantine Gatsonis
    • 1
  • Robert E. Kass
    • 2
  • Bradley Carlin
    • 3
  • Alicia Carriquiry
    • 4
  • Andrew Gelman
    • 5
  • Isabella Verdinelli
    • 6
  • Mike West
    • 7
  1. 1.Center for Statistical SciencesBrown UniversityProvidenceUSA
  2. 2.Department of StatisticsCarnegie Mellon UniversityPittsburghUSA
  3. 3.Division of BiostatisticsUniversity of MinnesotaMinneapolisUSA
  4. 4.Department of StatisticsIowa State UniversityAmesUSA
  5. 5.Department of StatisticsColumbia UniversityNew YorkUSA
  6. 6.Department of StatisticsCarnegie Mellon UniversityPittsburghUSA
  7. 7.Institute of Statistics and Decision SciencesDuke UniversityDurhamUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-1502-8
  • Copyright Information Springer-Verlag New York, Inc. 1999
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98640-1
  • Online ISBN 978-1-4612-1502-8
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site