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Testing dose-response relationships with a priori unknown, possibly nonmonotone shapes
1Department of Bioinformatics, University of Hannover, Germany. bretz@ifgb.uni-hannover.de
Abstract:
Usually, a monotone dose-response dependence can be assumed for the simultaneous comparison of increasing levels of a certain drug. However, sometimes a reversal of the dose-response curve is likely to occur at the higher doses. We investigate such violations of the monotonicity assumption. Adequate alternatives are discussed and the "protected trend alternative" is introduced. Together with the umbrella patterns described in the literature, we introduce new testing approaches for both alternatives. P-values/quantiles and power values/sample sizes are made numerically available and hence are readily computed. A short power study and the analysis of a data set from the literature demonstrate the improved behavior of the new methods.
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