est_full_stats: Estimate stats on the full samples

In microsoft/CausalGrid: Analysis of Subgroups

Estimate stats on the full samples

Description

Estimates the parameters on the full and est samples

Usage

est_full_stats(
  y,
  X,
  d,
  est_plan,
  y_es = NULL,
  X_es = NULL,
  d_es = NULL,
  index_tr = NULL,
  alpha = 0.05
)

Arguments

y	Nx1 matrix of outcome (label/target) data. With multiple core estimates see Details below.
X	NxK matrix of features (covariates). With multiple core estimates see Details below.
d	(Optional) NxP matrix (with colnames) of treatment data. If all equally important they should be normalized to have the same variance. With multiple core estimates see Details below.
est_plan	Estimator plan
y_es	y for est sample. Omit if providing index_tr.
X_es	X for est sample. Omit if providing index_tr.
d_es	d for est sample. Omit if providing index_tr.
index_tr	Indexes of the train sample. Can be omitted if providing y_es, X_es, d_es.
alpha	Significance threshold

Value

Stats df

Multiple estimates

With multiple core estimates (M) there are 3 options (the first two have the same sample across treatment effects).

1. DS.MULTI_SAMPLE: Multiple pairs of (Y_m,W_m). y,X,d are then lists of length M. Each element then has the typical size The N_m may differ across m. The number of columns of X will be the same across m.

2. DS.MULTI_D: Multiple treatments and a single outcome. d is then a NxM matrix.

3. DS.MULTI_Y: A single treatment and multiple outcomes. y is then a NXM matrix.

microsoft/CausalGrid documentation built on Aug. 25, 2022, 9:30 a.m.