interacted_linear_estimators: Interacted linear regression models

In lmiratrix/blkvar: ATE and Treatment Variation Estimation for Blocked and Multisite RCTs

Interacted linear regression models

Description

These linear models have block by treatment interaction terms. The final ATE estimates are then weighted average of the block (site) specific ATE estimates.

Usage

interacted_linear_estimators(
  Yobs,
  Z,
  B,
  siteID = NULL,
  data = NULL,
  control_formula = NULL
)

Arguments

Yobs	Name of outcome variable (assumed to exist in data)
Z	vector of assignment indicators (1==treated)
B	block ids
siteID	If not null, name of siteID that has randomization blocks
data	Dataframe of the data to analyse.
control_formula	The control_formula argument must be of the form ~ X1 + X2 + ... + XN. (nothing on left hand side of ~)

Details

#' If siteID passed, it will weight the RA blocks within site and then average these site estimates.

SEs come from the overall variance-covariance matrix.

Value

Dataframe of the different versions of this estimator (person and site weighted)

See Also

Other linear model estimators: fixed_effect_estimators(), linear_model_estimators(), weighted_linear_estimators()

lmiratrix/blkvar documentation built on Nov. 18, 2024, 1:27 p.m.