A dose-response study, which is performed to determine whether or not there is any effect of a new drug related to dose, plays a very important role in the clinical development of a drug. Finding evidence of the dose-response relationship is usually done based on hypothesis testing, which has been considered an appropriate way to analyze a dose-response study. Hypothesis testing does not provide information about certain structures of the dose-response relationship, especially the shape and location of the dose-response curve, though the information is most helpful in determining the clinical dose of a drug. In this paper, the model-based approach with data-adaptive distribution is introduced to infer the dose-response relationship. We also introduce the statistical descriptive use of the empirical cumulative distribution function. Furthermore, methods to compare two dose-response curves are considered.
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