Skip to contents

Estimate ATEs for a cluster RCT using linear model

Source: R/linear_model_estimators.R
interacted_linear_model_estimators.Rd

Estimate district-average effects using an interacted FE model and then aggregate.

Usage

interacted_linear_model_estimators(
  formula,
  data = NULL,
  control_formula = NULL,
  weight = c("Person", "Cluster"),
  use_full_vcov = 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".

weight

"Person" to weight the regression by individual (unweighted OLS), "Cluster" to weight so each cluster contributes equally (inverse cluster-size weights).

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?