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). |