BipartiteGroupIPW: Function that estimates the cluster average potential outcome...

In gpapadog/Interference: Causal inference with interference for realistic regimes

Function that estimates the cluster average potential outcome in settings of bipartite interference.

Description

Function that estimates the cluster average potential outcome in settings of bipartite interference.

Usage

BipartiteGroupIPW(
  int_dta,
  out_dta,
  cov_cols,
  phi_hat,
  alpha,
  trt_col = NULL,
  out_col = NULL,
  integral_bound = 10
)

Arguments

int_dta	Data on the interventional units including treatment, neighborhood index and covariates. Neighborhood variable should be named 'neigh' and only include continuous integers from 1 to the number of neighborhoods.
out_dta	Data on the outcome units including outcome, neighborhood, and index of the closest interventional unit as 'closest_int'. Neighborhood variable should be named 'neigh' and only include continuous integers from 1 to the number of neighborhoods.
cov_cols	The indices including the covariates of the ps model.
phi_hat	A list with two elements. The first one is a vector of coefficients of the ps, and the second one is the random effect variance.
alpha	The values of alpha for which we want to estimate the group average potential outcome.
trt_col	If the treatment is not named 'A' in int_dta, specify the treatment column index.
out_col	If the outcome is not named 'Y' in out_dta, specify the outcome column index.
integral_bound	The number of standard deviations of the random effect that will be used as the lower and upper limit. Defaults to 10.

gpapadog/Interference documentation built on Oct. 30, 2022, 9:20 p.m.