• Lawrence M. Friedman
  • Curt D. Furberg
  • David L. DeMets
  • David M. Reboussin
  • Christopher B. Granger


In any clinical trial bias in determining treatment effects is one of the main concerns. Bias may be defined as systematic error, or “difference between the true value and that actually obtained due to all causes other than sampling variability” [1]. It can be caused by conscious factors, subconscious factors, or both. Bias can occur at a number of places in a clinical trial, from the initial design through data analysis, interpretation and reporting. One general solution to the problem of bias is to keep the participants and the investigators blinded, or masked, to the identity of the assigned intervention. One can also blind several other aspects of a trial including the assessment, classification and evaluation of the response variables. A large sample size does not reduce bias.


International Normalize Ratio Monitoring Committee International Normalize Ratio Control Bismuth Citrate Ranitidine Hydrochloride 
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lawrence M. Friedman
    • 1
  • Curt D. Furberg
    • 2
  • David L. DeMets
    • 3
  • David M. Reboussin
    • 4
  • Christopher B. Granger
    • 5
  1. 1.North BethesdaUSA
  2. 2.Division of Public Health SciencesWake Forest School of MedicineWinston-SalemUSA
  3. 3.Department Biostatistics and Medical InformaticsUniversity of WisconsinMadisonUSA
  4. 4.Department of BiostatisticsWake Forest School of MedicineWinston-SalemUSA
  5. 5.Department of MedicineDuke UniversityDurhamUSA

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