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UID:20260207T065951EST-9717UCL1db@132.216.98.100
DTSTAMP:20260207T115951Z
DESCRIPTION:Bayesian Sample Size Determination for Clinical Trials\n\nSampl
 e size determination problem is an important task in the planning of clini
 cal trials. The problem may be formulated formally in statistical terms. T
 he most frequently used methods are based on the required size\, and power
  of the trial for a specified treatment effect. In contrast to the Bayesia
 n decision-theoretic approach\, there is no explicit balancing of the cost
  of a possible increase in the size of the trial against the benefit of th
 e more accurate information which it would give. In this talk a fully Baye
 sian approach to the sample size determination problem is discussed. This 
 approach treats the problem as a decision problem and employs a utility fu
 nction to find the optimal sample size of a trial. Furthermore\, we assume
  that a regulatory authority\, which is deciding on whether or not to gran
 t a licence to a new treatment\, uses a frequentist approach. The optimal 
 sample size for the trial is then found by maximising the expected net ben
 efit\, which is the expected benefit of subsequent use of the new treatmen
 t minus the cost of the trial.burn\n
DTSTART:20170324T193000Z
DTEND:20170324T203000Z
LOCATION:room 1205\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Hamid Pezeshik\, University of Tehran
URL:/mathstat/channels/event/hamid-pezeshik-university
 -tehran-267238
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