rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Statistical Monitoring of Clinical Trials
    sub title: A Unified Approach
  name:
    name part: Proschan, Michael A.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Lan, K. K. Gordan.
    role:
      role term: author.
  name:
    name part: Wittes, Janet Turk.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2006
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 268 p. 32 illus. online resource.
  abstract: The approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion (``the B-value") irrespective of the test statistic. The so-called B-value approach to monitoring allows us to use, for different types of trials, the same boundaries and the same simple formula for computing conditional power. Although Brownian motion may sound complicated, the authors make the approach easy by starting with a simple example and building on it, one piece at a time, ultimately showing that Brownian motion works for many different types of clinical trials. The book will be very valuable to statisticians involved in clinical trials. The main body of the chapters is accessible to anyone with knowledge of a standard mathematical statistics text. More mathematically advanced readers will find rigorous developments in appendices at the end of chapters. Reading the book will develop insight into not only monitoring, but power, survival analysis, safety, and other statistical issues germane to clinical trials. Michael Proschan, Gordon Lan, and Janet Wittes are elected Fellows of the American Statistical Association. All have spent formative years in the Biostatistics Research Branch of the National Heart, Lung, and Blood Institute (NHLBI/NIH). While there, they were intimately involved in the design and statistical monitoring of large-scale randomized clinical trials, developing methodology to aid in their monitoring. For example, Lan developed, with DeMets, the now widely-used spending function approach to group sequential designs, whose properties were further investigated by Proschan. The B-value …
  table of contents: A General Framework -- Power: Conditional, Unconditional, and Predictive -- Historical Monitoring Boundaries -- Spending Functions -- Practical Survival Monitoring -- Inference Following a Group-Sequential Trial -- Options When Brownian Motion Does Not Hold -- Monitoring for Safety -- Bayesian Monitoring -- Adaptive Sample Size Methods -- Topics Not Covered -- Appendix I: The Logrank and Related Tests -- Appendix II: Group-Sequential Software.
  note: by Michael A. Proschan, K. K. Gordan Lan, Janet Turk Wittes.
  subject:
    topic: Statistics
  subject:
    topic: Statistics
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Statistics for Biology and Health
  identifier: 9780387449708
  identifier: http://dx.doi.org/10.1007/978-0-387-44970-8
  record info:
    record creation date: 100301
    record change date: 20150207022356.0
    record identifier: 978-0-387-44970-8