Data-dependent contrast test for dose-finding clinical trials

We propose a simple and powerful data-dependent contrast test with ordinal-constraint contrast coefficients of the dose response determined from observed responses. The contrast coefficients are easily calculated using a pool-adjacent-violators algorithm and making assumptions for the contrast coefficients. Once the dose response is determined for p < 0.05 in the data-dependent contrast test, the best dose-response model is selected from multiple dose-response models. Using the best model, a recommended dose is identified. We demonstrate the data-dependent contrast test for sample data. In addition, we calculate the ordinal-constraint contrast coefficients and test statistic for an actual study, and we obtain a recommended dose. Finally, we perform a simulation study with 11 scenarios to evaluate the performance of the data-dependent contrast test by comparing multiple comparison procedures with modeling techniques.