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Quantifying the bias in the estimated treatment effect in randomized trials having interim analyses and a rule for early stopping for futility
Journal article

Quantifying the bias in the estimated treatment effect in randomized trials having interim analyses and a rule for early stopping for futility

  • Walter, S. D. ORCID Clinical Epidemiology and Biostatistics; McMaster University; Hamilton Ontario Canada
  • Han, H. Mathematics and Statistics; McMaster University; Hamilton Ontario Canada
  • Briel, M. Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research; University Hospital Basel; Switzerland
  • Guyatt, G. H. Clinical Epidemiology and Biostatistics and Medicine; McMaster University; Hamilton Ontario Canada
  • 2017-2-9
Published in:
  • Statistics in Medicine. - Wiley. - 2017, vol. 36, no. 9, p. 1506-1518
Statistics and Probability
Epidemiology
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/231884
Statistics
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