Data — T2-simulation
This project uses no observed data. The only input is design.csv, written by the task designer: the nine cells of the Monte Carlo design (one row per cell).
| column | meaning |
|---|---|
cell_id |
C1 … C9 |
G |
number of clusters (5, 10, 30) |
icc |
intra-cluster correlation of the data-generating process (0.0, 0.2, 0.5) |
cluster_sizes |
the G cluster sizes n_1, …, n_G, separated by ` |
N |
total number of observations in a sample |
R |
number of Monte Carlo replications per cell (2000) |
B |
number of wild-bootstrap draws per replication (399) |
seed |
the seed to use for the cell (numpy default_rng(seed) or equivalent) |
mu |
population mean of y (0.0) |
total_variance |
Var(y_ig) = Var(u_g) + Var(e_ig) = 1.0 |
nominal_level |
nominal confidence level (0.95) |
Data-generating process for a cell: y_ig = mu + u_g + e_ig, g = 1..G, i = 1..n_g, with u_g ~ N(0, icc) independent across clusters and e_ig ~ N(0, 1 − icc) independent across observations and of u. All simulated data are synthetic; nothing here is observed data.