Clinical trials simulation: A statistical approach

Peter H. Westfall, Kuenhi Tsai, Stephan Ogenstad, Alin Tomoiaga, Scott Moseley, Yonggang Lu

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

A generic template for clinical trials simulations that are typically required by statisticians is developed. Realistic clinical trials data sets are created using a unifying model that allows general correlation structures for endpoint*timepoint data and nonnormal distributions (including time-to-event), and computationally efficient algorithms are presented. The model allows for patient dropout and noncompliance. A grid-enabled SAS-based system has been developed to implement this model; details are presented summarizing the system development. An example illustrating use of the system is given.

Original languageEnglish
Pages (from-to)611-630
Number of pages20
JournalJournal of Biopharmaceutical Statistics
Volume18
Issue number4
DOIs
StatePublished - Jul 2008

Keywords

  • Binary data
  • Correlation structure
  • Grid computing
  • Mixture data
  • Non-compliance
  • Non-normality
  • Ordinal data
  • Patient dropouts
  • Survival data

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