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Estimate ATEs for cluster RCT using data aggregation.

Source: R/aggregation_estimators.R
aggregation_estimators.Rd

This method aggregates data at the cluster level, and analyzes using linear regression. Can optionally pass pre-aggregated data if desired.

Usage

aggregation_estimators(
  formula,
  data = NULL,
  control_formula = NULL,
  control_interacted = FALSE,
  aggregated = FALSE
)

Arguments

formula

Formula for outcome and treatment and nesting. If NULL, data is assumed to be in canonical form (see vignette for further discussion).

data

Data frame holding the outcome, treatment, and clustering/blocking columns referenced by `formula` (or already in canonical form if `formula` is NULL).

control_formula

What variables to control for, in the form of "~ X1 + X2".

control_interacted

If TRUE, also fit block-by-covariate interacted control models. Ignored if `control_formula` is NULL.

aggregated

TRUE means `data` is already aggregated to the cluster level (and in canonical form). FALSE means it is not and will be aggregated internally.

Details

This automatically does both weighting approaches.