Summary We investigate whether Bayesian decision theory, in the form of expected value of partial perfect information (EVPPI) analysis, is a realistic and practical approach to research prioritization. We develop a simple cost-effectiveness analysis of breast cancer screening as a typical case-study, motivated by data from a cluster randomized 2 × 2 factorial trial of interventions to increase uptake. An EVPPI analysis is developed which shows that, on the basis of the evidence that was available beforehand, the trial was cost effective, but that after incorporating the results of the trial it would still be cost effective to carry out research that further reduced decision uncertainty. We identify key conceptual and technical issues: the relationship between the target interventions and the previous evidence, the distinction between variation and uncertainty and methods for correlated parameters. EVPPI methods have clear advantages over current methods of research prioritization, but we suggest that some specific sensitivity analyses are required before they can be used confidently in practice. These have limitations, and there is a need to develop robust methods to optimize research portfolios.

Teaching StatisticsVolume 16, Issue 2 p. 45-46 Teaching Statistics in Victorian England-The Other Side Of a Darwinian Coin? Part 2 John Bibby, John Bibby QED, York and Sheffiedld Hallam University.Search for more papers by this author John Bibby, John Bibby QED, York and Sheffiedld Hallam University.Search for more papers by this author First published: June 1994 https://doi.org/10.1111/j.1467-9639.1994.tb00686.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume16, Issue2June 1994Pages 45-46 RelatedInformation

On December 6th, 1989, Sir Jack Hibbert opened a discussion meeting at the Royal Statistical Society (RSS) on Public Confidence in the Integrity and Validity of Official Statistics. Several speakers suggested a UK National Statistical Commission could alleviate some of the perceived problems with official statistics. An RSS Working Party (whose membership was announced at the meeting) examined, inter alia, the merits of such a Commission and one of its recommendations in its July 1990 report was that the UK should set up a National Statistical Commission. As a basis for a fuller discussion of the Working Party's recommendation for a UK National Statistical Commission, this short paper outlines the role, construction and operation of similar Commissions in various countries, putting forward a possible model for such a Commission in the UK.

Teaching StatisticsVolume 14, Issue 1 p. 16-17 Report of a Colloquium John Bibby, QED Consultants, YorkSearch for more papers by this author John Bibby, QED Consultants, YorkSearch for more papers by this author First published: March 1992 https://doi.org/10.1111/j.1467-9639.1992.tb00201.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume14, Issue1March 1992Pages 16-17 RelatedInformation

Teaching StatisticsVolume 13, Issue 2 p. 38-39 Karl Pearson and the History of Teaching Statistics John Bibby, John Bibby QED Consultants and York UniversitySearch for more papers by this author John Bibby, John Bibby QED Consultants and York UniversitySearch for more papers by this author First published: June 1991 https://doi.org/10.1111/j.1467-9639.1991.tb00160.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume13, Issue2June 1991Pages 38-39 RelatedInformation

Think and Explain with Statistics. By L. E. Moses. ISBN 0 201 15619 9. Addison‐Wesley, New York, 1986. xii + 484 pp.

Biometrical JournalVolume 30, Issue 5 p. 606-606 Book Review Bibby, J. (Compiler): ‘Quotes, Damned Quotes, and…’ (2nd Edition), John Bibby (Books), Edinburgh, Scotland, 1986, 50 pages, $ 2.50 J. Bibby, 29 Liberton Brae, Edinburgh EH16 6AG, ScotlandSearch for more papers by this author J. Bibby, 29 Liberton Brae, Edinburgh EH16 6AG, ScotlandSearch for more papers by this author First published: 1988 https://doi.org/10.1002/bimj.4710300517AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume30, Issue51988Pages 606-606 RelatedInformation