estimate_ATE_RIRC_pool: Fit Random-intercept, random-slope model

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

Fit Random-intercept, random-slope model

Description

This is a wrapper for a simpler lmer call.

Usage

estimate_ATE_RIRC_pool(
  Yobs,
  Z,
  B,
  data = NULL,
  REML = FALSE,
  include_testing = TRUE,
  keep_EB_estimates = TRUE,
  control_formula = NULL
)

Arguments

Yobs	Name of outcome variable (assumed to exist in data)
Z	vector of assignment indicators (1==treated)
B	Name of the block indicator.
data	Dataframe with all needed variables.
REML	Logical, Restricted maximum likelihood or maximum likelihood estimation. Default of TRUE if include_testing = FALSE and FALSE otherwise. Note that FIRC can fail badly in estimating cross-site variation when REML=FALSE.
include_testing	Logical Include likelihood ratio test for cross-site treatment variation.
keep_EB_estimates	TRUE means returned object has EB estimates. FALSE means do not keep them.
control_formula	The control_formula argument must be of the form ~ X1 + X2 + ... + XN. (nothing on left hand side of ~)

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