School of Mathematical Sciences

Order restricted inference for multi-arm trials menu

Order restricted inference for multi-arm trials

Speaker: 
Muna Arephin
Cancer Research UKCentre for Epidemiology, Mathematics and StatisticsWolfson Institute of Preventive MedicineCharterhouse Square
Date/Time: 
Thu, 11/03/2010 - 16:30
Room: 
M203
Seminar series: 

There is an increasing demand to test more than one new treatment in the hope of
finding at least one that is better than the control group in clinical trials. A likelihood
ratio test is developed using order restricted inference, a family of tests is defined and
it is shown that the LRT and Dunnett-type tests are members of this family. Tests are
compared, using power and a simple loss function which takes incorrect selection, and
its impact, into account. The optimal allocation of patients to treatments were sought
to maximize power and minimize expected loss.

For small samples, the LRT statistic for binary data based on order restricted inference
is derived and used to develop a conditional exact test. Two-stage adaptive designs for
comparing two experimental arms with a control are developed, in which the trial is
stopped early if the difference between the best treatment and the control is less than
C1; otherwise, it continues, with one arm if one experimental treatment is better than
the other by at least C2, or with both arms otherwise. Values of the constants C1 and
C2 are compared and the adaptive design is found to be more powerful than the fixed
design.