Average block-level estimates to get overall ATE — generate_all_interacted

Also calculate associated standard error.

Usage

generate_all_interacted_estimates(
  fitModel,
  data,
  use_full_vcov = FALSE,
  SE_table = NULL,
  method = "LR",
  weight = NULL,
  se_method = "crve",
  aggregated = FALSE,
  include_block_estimates = FALSE
)

Arguments

fitModel: The model that has the interacted estimates in it.
data: Data frame the model was fit on (in canonical form).
use_full_vcov: TRUE/FALSE. When calculating standard errors, should the full variance-covariance matrix of the block-level estimates be used, or just the diagonal of standard errors?
SE_table: Optional precomputed table of block-level standard errors to use instead of extracting them from `fitModel`.
method: Prefix of the method. Will add the weighting to stem.
weight: "Person" or "Cluster" weighting used when averaging block-level estimates to an overall ATE.
se_method: Which standard error method the block-level estimates in `fitModel`/`SE_table` were computed with (e.g. "crve", "het", "db"). Used only for labeling.
aggregated: TRUE means data is summarized at the Block level. False means it is not, and needs to be aggregated.
include_block_estimates: If TRUE, also return the block-by-block estimates used to build the overall estimate, in addition to the aggregate estimate.