American Statistical Association
New York City
Metropolitan Area Chapter

Mailman School of Public Health
Columbia University
Department of Biostatistics Colloquium



Gordon Lan
Johnson & Johnson


A brief overview of adaptive design will be given, with emphasis on alpha control and two-stage winner design. The use of normal approximation to control alpha was presented at Columbia in 2003. This time, we extend the results to sample size and power evaluations. We consider a study starting with two dose levels: A, B and a placebo control C. A loser between A and B will be dropped at the end of Stage I, and the winner will be compared with C at the end of Stage II. To control alpha, one may use numerical integration to directly evaluate the critical value for the test statistic. Fortunately, normal approximation to this statistic is good enough for most practical situations and fine-tuning of the approximation requires only a very simple modification of the p-values. Power evaluation is more complicated when A and B have different treatment effects. We will demonstrate that with appropriate modifications, normal approximation gives very accurate estimates for power and sample size evaluation.

Date: Tuesday, February 13, 2007
Time: 2:00 to 3:00 P.M.
Location: Note new location:
New York State Psychiatric Institute
Room 4001
1051 Riverside Drive
New York, New York

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