View source: R/attgt_functions.R
| pte_attgt | R Documentation | 
pte_attgt takes a "local" data.frame and computes
an estimate of a group time average treatment effect
and a corresponding influence function.  This function generalizes
a number of existing methods.
The code relies on this.data having certain variables defined.
In particular, there should be an id column (individual identifier),
G (group identifier), period (time period), name
(equal to "pre" for pre-treatment periods and equal to "post" for post
treatment periods), Y (outcome).
In our case, we call pte::two_by_two_subset which sets up the
data to have this format before the call to pte_attgt
pte_attgt(
  gt_data,
  xformla,
  d_outcome = FALSE,
  d_covs_formula = ~-1,
  lagged_outcome_cov = FALSE,
  est_method = "dr",
  ...
)
gt_data | 
 data that is "local" to a particular group-time average treatment effect  | 
xformla | 
 one-sided formula for covariates used in the propensity score and outcome regression models  | 
d_outcome | 
 Whether or not to take the first difference of the outcome. The default is FALSE. To use difference-in-differences, set this to be TRUE.  | 
d_covs_formula | 
 A formula for time varying covariates to enter the first estimation step models. The default is not to include any, and, hence, to only include pre-treatment covariats.  | 
lagged_outcome_cov | 
 Whether to include the lagged outcome as a covariate. Default is FALSE.  | 
est_method | 
 Which type of estimation method to use. Default is "dr" for doubly robust. The other option is "reg" for regression adjustment.  | 
... | 
 extra function arguments; not used here  | 
attgt_if
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