Table 2.

Generic key questions with suggested models used for addressing the questions

Type	Question	Analysis*
A	Does data indicate a treatment effect?	ECFB ∼ EBASE + COVs + Slope*Exposure +Intercept (analysis based on all data)
B	Does treatment effect increase with dose?	ECFB ∼ EBASE + COVs + Slope*Exposure +Intercept (data from placebo excluded)
C	What are the characteristics of the E-R relationship? What is the predicted effect of dose changes?	+Intercept, (analysis based on all data)

^*E_CFB indicates the change from baseline of the primary endpoint, E_BASE is the baseline value of the effect variable. Exposure is an exposure variable such as the area under the concentration-time curve in a dosing interval at steady-state. COV is the contribution from covariates for the effect. Slope is the estimated slope of the E-R relationship on a linear scale. The E_max model (Type C) is parameterized by E_max, the maximal effect obtained at infinite exposure and EC₅₀, the exposure at half-maximal effect. For any of the analysis, an intercept, representing the response at zero exposure (i.e., placebo) is included. The equations are written with E_CFB as the dependent variable, assuming a continuous endpoint. Similar analyses may be applied for categorical binary endpoints, following logit transformation, and using the response rate as the dependent variable.