`get_est()` generates causal estimates comparing two counterfactual scenarios.
get_est(
obs,
cf1,
cf2,
treat,
sm_out,
mediation = FALSE,
obs_med_log_sum_dens = NA,
cf1_med_log_sum_dens = NA,
cf2_med_log_sum_dens = NA,
lag,
time_after = TRUE,
entire_window,
use_dist,
windows,
dist_map,
dist,
trunc_level = NA,
save_weights = TRUE
)list of the following: `cf1_ave_surf`: average weighted surface for scenario 1 `cf2_ave_surf`: average weighted surface for scenario 2 `est_cf`: estimated effects of each scenario `est_causal`: estimated causal contrasts `var_cf`: variance upper bounds for each scenario `var_causal`: variance upper bounds for causal contrasts `windows`: list of owin objects
observed density
counterfactual density 1
counterfactual density 2
column of a hyperframe that summarizes treatment data. In the form of `hyperframe$column`.
column of a hyperframe that summarizes the smoothed outcome data
whether to perform causal mediation analysis (don't use; still in development). By default, FALSE.
sum of log densities of mediators for the observed (don't use; still in development)
sum of log densities of mediators for counterfactual 1 (don't use; still in development)
sum of log densities of mediators for counterfactual 2 (don't use; still in development)
integer that specifies lags to calculate causal estimates
whether to include one unit time difference between treatment and outcome. By default = TRUE
owin object (the entire region of interest)
whether to use distance-based maps. By default, TRUE
a list of owin objects (if `use_dist = FALSE`)
distance map (an im object, if `use_dist = TRUE`)
distances (a numeric vector within the max distance of `dist_map`)
the level of truncation for the weights (0-1)
whether to save weights
The level of truncation indicates the quantile of weights at which weights are truncated. That is, if `trunc_level = 0.95`, then all weights are truncated at the 95 percentile of the weights.