learn_clustering_se

source

learn_clustering_se(n_clusters=40, cluster_size=30, icc=0.3, seed=0)

Show that clustering changes the standard error, not the point estimate.

Simulates data with cluster-correlated regressor and errors (intra-cluster correlation icc), then compares classical (iid) standard errors with cluster-robust ones for the same coefficient.

Parameters

Name	Type	Description	Default
n_clusters	int	Number of clusters and observations per cluster.	`40`
cluster_size	int	Number of clusters and observations per cluster.	`40`
icc	float	Intra-cluster correlation of the errors (drives the standard-error inflation).	`0.3`
seed	int	Random seed.	`0`

Returns

Name	Type	Description
	SandboxResult	`df` (iid vs clustered standard error), `fig`, `summary` and `topic`.

Examples

This sandbox simulates its own clustered data, so the call needs no DataFrame:

import expdpy as ex

res = ex.learn_clustering_se()
res.fig