| EquiTrends-package | Equivalence Testing for Pre-Trends in Difference-in-Differences Designs |
| boot_optimization_function | Finding the restricted placebo coefficients for the maximum equivalence test based on the bootstrap approaches |
| EquiTrends | Equivalence Testing for Pre-Trends in Difference-in-Differences Designs |
| EquiTrends_dataconstr | Data Construction Function for EquiTrends |
| EquiTrends_inputcheck | Input Checks Function for EquiTrends |
| maxEquivTest | Equivalence Test for Pre-trends based on the Maximum Absolute Placebo Coefficient |
| maxTestBoot_func | An internal function of the EquiTrends Maximum Equivalence Testing procedure using the Bootstrap approaches. |
| maxTestIU_func | An internal function of the EquiTrends Maximum Equivalence Testing procedure using the Intersection Union approach. |
| maxTestIU_optim_func | Finding the minimum equivalence threshold for the equivalence test based on the IU procedure for the maximum placebo coefficient. |
| maxTest_error | Additional input checks for the maxEquivTest function |
| meanEquivTest | Equivalence Test for Pre-trends based on the Mean Placebo Coefficient |
| meanTest_func | An internal function of the EquiTrends Mean Equivalence Testing procedure |
| meanTest_optim_func | Finding the minimum equivalence threshold for the mean equivalence test |
| print.maxEquivTestBoot | Print maxEquivTestBoot objects |
| print.maxEquivTestIU | Print maxEquivTestIU objects |
| print.meanEquivTest | Print meanEquivTest objects |
| print.rmsEquivTest | Print rmsEquivTest objects |
| rmsEquivTest | Equivalence Test for Pre-trends based on the RMS Placebo Coefficient |
| rmsTest_error | Additional input checks for the rmsEquivTest function |
| rmsTest_func | An internal function of the RMS Equivalence Testing procedure |
| sigma_hathat_c | Calculating the constrained variance of the residuals for the Boostrap approaches in the EquiTrends Maximum Equivalence Testing procedure, according to Dette & Schumann (2024). |
| sim_check | Checking input for the sim_paneldata function |
| sim_paneldata | Simulating a panel data for a binary treatment |
| W_critical_value | Calculating the critical value for the W distribution as construced in Dette & Schumann (2024). |