sim.CATE: Simulate a dataset with known constant CATE
In tlverse/causalglm: Interpretable and robust causal inference for heterogeneous treatment effects using generalized linear models with targeted machine-learning.
sim.CATE R Documentation
Simulate a dataset with known constant CATE
Description
Simulate a dataset with known constant CATE
Usage
sim.CATE(
n = 1500,
p = 2,
prop_active = 1,
sigma = NULL,
formula_estimand = ~1,
formula_A = ~.,
formula_Y0W = ~.,
beta = NULL,
beta_A = NULL,
beta_Y = NULL
)
Arguments
n
Sample size
p
Dimension of W
prop_active
Proportion of active (nonzero coef) variables
tlverse/causalglm documentation built on April 15, 2022, 6:35 p.m.
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| sim.CATE | R Documentation |
Simulate a dataset with known constant CATE
Description
Simulate a dataset with known constant CATE
Usage
sim.CATE( n = 1500, p = 2, prop_active = 1, sigma = NULL, formula_estimand = ~1, formula_A = ~., formula_Y0W = ~., beta = NULL, beta_A = NULL, beta_Y = NULL )
Arguments
n |
Sample size |
p |
Dimension of W |
prop_active |
Proportion of active (nonzero coef) variables |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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