generate_dataset {BayesRegDTR} | R Documentation |
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)
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 |
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
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)
[Package BayesRegDTR version 1.0.1 Index]