crtAddIntervention: Add a New Intervention Group to Clustered Randomized Trial (CRT)

Description

This function adds a new intervention group to an existing CRT dataset. It models post-test outcomes using fixed and random effects estimated from the original data and incorporates user-specified effect size and attrition for the new intervention.

Usage

crtAddIntervention(
  originalData,
  ns,
  np,
  es,
  attritionrate,
  outcome,
  interventions,
  schoolsID,
  pupilsID,
  continuous_covariates,
  categorical_covariates
)

Value

A data.frame combining the original and new intervention group, including post-test outcomes simulated for the new intervention based on the estimated mixed model.

Arguments

originalData: A data frame containing the variables including outcome, predictors, the clustering variable, and the intervention for CRT design.
ns: The number of schools to assign to the new intervention group.
np: The number of pupils per new school.
es: The standardized effect size for the new intervention group.
attritionrate: The proportion of pupils in the new group to drop due to attrition.
outcome: A string specifying the name of the column containing outcome variable (e.g., post-test scores).
interventions: A string specifying the name of the intervention assignment column.
schoolsID: A string specifying the name of the school ID column.
pupilsID: A string specifying the name of the pupil ID column.
continuous_covariates: A character vector specifying the names of continuous covariates in the model.
categorical_covariates: A character vector specifying the names of categorical covariates in the model (converted to factors).

Details

The function performs the following:

Fits a linear mixed-effects model (lmer) to the original dataset using provided covariates.
Applies the specified effect size (es) and generates new post-test scores.
Simulates attrition by removing post-test scores at random.

Examples

Run this code

data(crt4armSimData)
new_crt5armData <- crtAddIntervention(originalData = crt4armSimData, ns = 2,
np = 100, es = 0.3, attritionrate = 0.1, outcome = "posttest", interventions = "interventions", 
schoolsID = "schools", pupilsID = "pupils", 
continuous_covariates = c("pretest"), categorical_covariates = c("gender", "ethnicity"))
head(new_crt5armData)