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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