data_backdoor: Data generated from a classic backdoor model, where the...
In flexCausal: Causal Effect Estimation via Doubly Robust One-Step Estimators and TMLE in Graphical Models with Unmeasured Variables
data_backdoor R Documentation
Data generated from a classic backdoor model, where the pre-treatment variable X cause A and Y, and the treatment A cause Y.
Description
Data generated from a classic backdoor model, where the pre-treatment variable X cause A and Y, and the treatment A cause Y.
Usage
data_backdoor
Format
A data frame with 2000 rows and 3 variables: X, A, Y.
- X
a variable that follows uniform distribution at the interval of [0,1]
- A
a binary treatment
- Y
a variable that follows normal distribution
References
flexCausal documentation built on March 29, 2026, 5:08 p.m.
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| data_backdoor | R Documentation |
Data generated from a classic backdoor model, where the pre-treatment variable X cause A and Y, and the treatment A cause Y.
Description
Data generated from a classic backdoor model, where the pre-treatment variable X cause A and Y, and the treatment A cause Y.
Usage
data_backdoor
Format
A data frame with 2000 rows and 3 variables: X, A, Y.
- X
a variable that follows uniform distribution at the interval of
[0,1]- A
a binary treatment
- Y
a variable that follows normal distribution
References
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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