Let's say that a treatment A has been proven to have an impact on the levels of B with a given confidence interval. Let's also say that we know that the treatment C causes the treatment A to be imposed on our sample. Before the testing on the effects of C has been done, which statistical models allow one to estimate the effects of the C treatment before hypothesis testing given these conditions? And the magnitude of the said effects, their likelihood, etc.? Is such an application of rationalism even appropriate in science?