crtDataSimulation: Simulate Clustered Randomized Trial (CRT) Data

In epts: Educational Platform Trials Simulator

Simulate Clustered Randomized Trial (CRT) Data

Description

This function simulates a multiple intervention arms CRT data. The model includes intervention and pre-test scores as covariates.

Usage

crtDataSimulation(
  ni,
  nstreated,
  np,
  ns,
  sigma,
  ICC,
  B0,
  es,
  seed,
  attritionrates,
  covariates
)

Arguments

ni	The number of intervention groups excluding the control group.
nstreated	The number of schools in each group, including the control group. It should be specified as an integer vector of length ni + 1.
np	The number of pupils per school.
ns	The total number of schools.
sigma	The standard deviation of the individual-level error.
ICC	The intra-class correlation coefficient.
B0	The intercept of the model.
es	The standardized effect sizes for each intervention group. It should be specified as a numeric vector.
seed	The random seed for reproducibility.
attritionrates	The proportion of attrition for each group, including the control group. It should be specified as a numeric vector of length ni + 1.
covariates	List of covariate specifications. Each element should be a list with the following fields: name Character. Name of the covariate. type Character. Either "continuous" or "categorical". sd Numeric. Standard deviation (only for continuous covariates). coefficient Numeric. Coefficient (only for continuous covariates). levels Character vector. Category levels (only for categorical covariates). probs Numeric vector. Sampling probabilities (must sum to 1) (categorical only). reference Character. Reference category (categorical only). coefficients Named list of numeric values. Coefficients for each non-reference level.

Value

A data.frame containing:

pupils

Unique pupil ID

schools

School ID

interventions

Intervention group (0 = control, 1 to ni for interventions)

covariates

Simulated covariates

posttest

Simulated posttest scores (NA if attrited)

Examples

covariates <- list(
 list(name = "pretest", type = "continuous", sd = 1, coefficient = 1.7),
 list(name = "gender", type = "categorical", levels = c("Male", "Female"),
 probs = c(0.3, 0.7), reference = "Male", coefficients = list(B = -0.5)),
 list(name = "ethnicity", type = "categorical", levels = c("White", "Black", "Asian"),
 probs = c(0.3, 0.3, 0.4), reference = "White", coefficients = list(B = 1.02, C = 1.3))
)

crtdata <- crtDataSimulation(ni = 3, ns = 10, np = 100, nstreated = c(2, 3, 2, 3), 
sigma = 1, ICC = 0.1, B0 = 1.45, es = c(0.1, 0.2, 0.5), 
seed = 1234, attritionrates = c(0, 0.1, 0.2, 0.1), covariates = covariates)
head(crtdata)

epts documentation built on June 8, 2025, 11:04 a.m.