An internal function that builds simulated data, computes
ATT(g,t)'s and some aggregations. It is useful for testing the inference
procedures in the did function.
Usage
sim(
sp_list,
ret = NULL,
bstrap = TRUE,
cband = TRUE,
control_group = "nevertreated",
xformla = ~X,
est_method = "dr",
clustervars = NULL,
panel = TRUE
)Arguments
- sp_list
A list of simulation parameters. See
reset.simto generate some default values for parameters- ret
which type of results to return. The options are
Wpval(returns 1 if the p-value from a Wald test that all pre-treatment ATT(g,t)'s are equal is less than .05),cband(returns 1 if a uniform confidence band covers 0 for groups and times),simple(returns 1 if, using the simple treatment effect aggregation results in rejecting that this aggregated treatment effect parameter is equal to 0),dynamic(returns 1 if the uniform confidence band from the dynamic treatment effect aggregation covers 0 in all pre- and post-treatment periods). The default value is NULL, and in this case the function will just return the results from the call toatt_gt.- bstrap
whether or not to use the bootstrap to conduct inference (default is TRUE)
- cband
whether or not to compute uniform confidence bands in the call to
att_gt(the default is TRUE)- control_group
Whether to use the "nevertreated" comparison group (the default) or the "notyettreated" as the comparison group
- xformla
Formula for covariates in
att_gt(default is~X)- est_method
Which estimation method to use in
att_gt(default is "dr")- clustervars
Any additional variables which should be clustered on
- panel
whether to simulate panel data (the default) or otherwise repeated cross sections data