get_est {geocausal}

Get causal estimates comparing two scenarios

Description

'get_est()' generates causal estimates comparing two counterfactual scenarios.

Usage

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
)

Arguments

obs

observed density

cf1

counterfactual density 1

cf2

counterfactual density 2

treat

column of a hyperframe that summarizes treatment data. In the form of 'hyperframe$column'.

sm_out

column of a hyperframe that summarizes the smoothed outcome data

mediation

whether to perform causal mediation analysis (don't use; still in development). By default, FALSE.

obs_med_log_sum_dens

sum of log densities of mediators for the observed (don't use; still in development)

cf1_med_log_sum_dens

sum of log densities of mediators for counterfactual 1 (don't use; still in development)

cf2_med_log_sum_dens

sum of log densities of mediators for counterfactual 2 (don't use; still in development)

lag

integer that specifies lags to calculate causal estimates

time_after

whether to include one unit time difference between treatment and outcome. By default = TRUE

entire_window

owin object (the entire region of interest)

use_dist

whether to use distance-based maps. By default, TRUE

windows

a list of owin objects (if 'use_dist = FALSE')

dist_map

distance map (an im object, if 'use_dist = TRUE')

dist

distances (a numeric vector within the max distance of 'dist_map')

trunc_level

the level of truncation for the weights (0-1)

Details

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.

Value

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