A novel model-checking approach for dose-response relationships

We propose a test for assessing nonlinear dose-response models based on a Crámer-von Mises statistic. We establish the asymptotic distribution of the test and demonstrate that the test can detect the local alternative converging to the null at the parametric rate $$. We provide a bootstrap resampling technique to calculate the critical values. It is observed that the test has good power performance in small sample sizes. We apply the proposed method to analyze 250 datasets from a pharmacologic study and conduct two small simulation experiments to explore the numerical performance of the proposed test and compare one commonly used test in practice.