BayesRegDTR (version 1.1.2)

generate_dataset: Generate a toy dataset in the right format for testing BayesLinRegDTR.model.fit

Description

Generates a toy dataset simulating observed data of treatments over time with final outcomes and intermediate covariates. Follows the method outlined in Toy-Datagen on Github

Usage

generate_dataset(n, num_stages, p_list, num_treats)

Value

Observed data organised as a list of \(\{y, X_1, X_2..., X_{num\_stages}, A\}\) where y is a vector of the final outcomes, \(X_1, X_2..., X_{num\_stages}\) is a list of matrices of the intermediate covariates and A is an \(n \times num\_stages\) matrix of the assigned treatments

Arguments

n

Number of samples/individuals to generate

num_stages

Total number of stages per individual

p_list

Vector of dimension for each stage

num_treats

Vector of number of treatment options at each stage

Examples

# -----------------------------
# Initialise Inputs
# -----------------------------
n           <- 5000
num_stages  <- 3
p_list_uvt  <- rep(1, num_stages)
p_list_mvt  <- c(1, 3, 3)
num_treats  <- rep(3, num_stages)

# -----------------------------
# Main
# -----------------------------
Data_uvt    <- generate_dataset(n, num_stages, p_list_uvt, num_treats)
Data_mvt    <- generate_dataset(n, num_stages, p_list_mvt, num_treats)