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Multiple Test Procedures for Dose Finding
Ajit C. Tamhane, Yosef Hochberg and Charles W. Dunnett
Vol. 52, No. 1 (Mar., 1996), pp. 21-37
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2533141
Page Count: 17
You can always find the topics here!Topics: Dosage, Dose response relationship, Mathematical procedures, Simulations, Biometrics, Critical points, Statistics, Applied statistics, Sample size, T distribution
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The problem of identifying the lowest dose level for which the mean response differs from that at the zero dose level is considered. A general framework for stepwise testing procedures that use contrasts among the dose level means is proposed. Using this framework, several new procedures are derived. These and some existing procedures, including that of Williams (1971, Biometrics 27, 103-117; 1972, Biometrics 28, 519-531), are compared analytically and by an extensive simulation study for the normal theory balanced one-way layout case. It is pointed out that the procedures based on the so-called step and basin contrasts proposed by Ruberg (1989, Journal of American Statistical Association 84, 816-822) have excessively high type I familywise error rates (FWEs) and, hence, they should not be used. Some findings of the simulation study are as follows: For monotone dose mean configurations, Williams' procedure and two step-down test procedures based on Helmert and linear contrasts offer the best performance. For nonmonotone dose mean configurations, the performance of Williams' procedure does degrade somewhat, but the other two procedures are still the best. For more complex designs, a simple step-down test procedure that uses any α-level tests (not necessarily t-tests) to compare each dose level with the zero dose level controls the FWE and is the only alternative available, but its power is rather low, especially under nonmonotone configurations. Step-up procedures are generally dominated by step-down procedures when the same contrasts are used although the differences are not great.
Biometrics © 1996 International Biometric Society